{"jobs":[{"id":"8bd52610-175c-42a7-a7cd-b29c45f9d305","title":"Research Engineer - Distributed Training","department":"Research","team":"Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:43:34.749+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/8bd52610-175c-42a7-a7cd-b29c45f9d305","applyUrl":"https://jobs.ashbyhq.com/primeintellect/8bd52610-175c-42a7-a7cd-b29c45f9d305/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">We train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models — compute, large-scale RL, environments, sandboxes, evals, and deployment.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Semianalysis, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2>What You’ll Work On</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and optimize the distributed training infrastructure behind our pre-training and large-scale RL training workloads by contributing to our <a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://github.com/PrimeIntellect-ai/prime-rl\">prime-rl</a> framework.</p></li><li><p style=\"min-height:1.5em\">Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.</p></li><li><p style=\"min-height:1.5em\">Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.</p></li><li><p style=\"min-height:1.5em\">Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.</p></li><li><p style=\"min-height:1.5em\">Help shape the architecture of our RL training stack, including async rollout and post-training systems.</p></li><li><p style=\"min-height:1.5em\">Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.</p></li><li><p style=\"min-height:1.5em\">Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.</p></li><li><p style=\"min-height:1.5em\">Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.</p></li></ul><h2></h2><h2>You May Be a Fit If You Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.</p></li><li><p style=\"min-height:1.5em\">Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.</p></li><li><p style=\"min-height:1.5em\">Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.</p></li><li><p style=\"min-height:1.5em\">Strong understanding of GPU architecture, profiling, and performance debugging.</p></li><li><p style=\"min-height:1.5em\">Ability to identify bottlenecks across the stack and drive improvements from first principles.</p></li><li><p style=\"min-height:1.5em\">Comfort working in a fast-moving environment with ambiguous problems and high ownership.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Especially Exciting</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience writing or optimizing CUDA / Triton kernels.</p></li><li><p style=\"min-height:1.5em\">Experience with compiler or runtime optimization for ML systems.</p></li><li><p style=\"min-height:1.5em\">Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.</p></li><li><p style=\"min-height:1.5em\">Experience with multi-node GPU clusters and high-performance networking.</p></li><li><p style=\"min-height:1.5em\">Contributions to open-source ML systems or infrastructure projects.</p></li><li><p style=\"min-height:1.5em\">Interest in publishing technical work or sharing insights through engineering blogs and technical writing.</p></li></ul><p style=\"min-height:1.5em\"></p><h2></h2><h2><strong><u>Benefits &amp; Perks</u></strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150-350k, plus equity incentives, aligning your success with the growth and impact of Prime Intellect.</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation assistance for international candidates.</p></li><li><p style=\"min-height:1.5em\">Quarterly team off-sites, hackathons, conferences and learning opportunities.</p></li><li><p style=\"min-height:1.5em\">Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.</p></li></ul><p style=\"min-height:1.5em\">If you’re excited about building the systems foundation for frontier-scale training and open superintelligence, we’d love to hear from you.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nWe train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models — compute, large-scale RL, environments, sandboxes, evals, and deployment.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Semianalysis, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nWHAT YOU’LL WORK ON\n\n - Build and optimize the distributed training infrastructure behind our pre-training and large-scale RL training workloads by contributing to our prime-rl https://github.com/PrimeIntellect-ai/prime-rl framework.\n\n - Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.\n\n - Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.\n\n - Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.\n\n - Help shape the architecture of our RL training stack, including async rollout and post-training systems.\n\n - Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.\n\n - Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.\n\n - Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.\n\n\n\n\n\nYOU MAY BE A FIT IF YOU HAVE\n\n - Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.\n\n - Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.\n\n - Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.\n\n - Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.\n\n - Strong understanding of GPU architecture, profiling, and performance debugging.\n\n - Ability to identify bottlenecks across the stack and drive improvements from first principles.\n\n - Comfort working in a fast-moving environment with ambiguous problems and high ownership.\n\n\n\n\nESPECIALLY EXCITING\n\n - Experience writing or optimizing CUDA / Triton kernels.\n\n - Experience with compiler or runtime optimization for ML systems.\n\n - Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.\n\n - Experience with multi-node GPU clusters and high-performance networking.\n\n - Contributions to open-source ML systems or infrastructure projects.\n\n - Interest in publishing technical work or sharing insights through engineering blogs and technical writing.\n\n\n\n\n\n\n\nBENEFITS & PERKS\n\n - Cash Compensation Range of $150-350k, plus equity incentives, aligning your success with the growth and impact of Prime Intellect.\n\n - Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.\n\n - Visa sponsorship and relocation assistance for international candidates.\n\n - Quarterly team off-sites, hackathons, conferences and learning opportunities.\n\n - Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.\n\nIf you’re excited about building the systems foundation for frontier-scale training and open superintelligence, we’d love to hear from you."},{"id":"ee13090e-3fea-40f0-b785-19316f52bf08","title":"Research Engineer - Reinforcement Learning","department":"Research","team":"Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:43:44.607+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/ee13090e-3fea-40f0-b785-19316f52bf08","applyUrl":"https://jobs.ashbyhq.com/primeintellect/ee13090e-3fea-40f0-b785-19316f52bf08/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><strong>Responsibilities</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Lead and participate in novel research to build a massive scale synthetic data generation pipeline and orchestration solution</p></li><li><p style=\"min-height:1.5em\">Optimize the performance, cost, and resource utilization of AI inference workloads by leveraging the most recent advances for compute &amp; memory optimization techniques.</p></li><li><p style=\"min-height:1.5em\">Contribute to the development of our open-source libraries and frameworks for synthetic data generation and distributed RL frameworks.</p></li><li><p style=\"min-height:1.5em\">Publish research in top-tier AI conferences such as ICML &amp; NeurIPS.</p></li><li><p style=\"min-height:1.5em\">Distill highly technical project outcomes in layman approachable technical blogs to our customers and developers.</p></li><li><p style=\"min-height:1.5em\">Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, synthetic data gen research and proactively identify opportunities to enhance our platform's capabilities and user experience.</p></li></ul><h2><strong>Requirements</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong background in AI/ML engineering, with extensive experience in designing and implementing end-to-end pipelines for the inference or training of large-scale AI models.</p></li><li><p style=\"min-height:1.5em\">Deep expertise in distributed inference techniques and frameworks (e.g. vllm, sglang) for optimizing the performance and scalability of AI workloads.</p></li><li><p style=\"min-height:1.5em\">Solid understanding of MLOps best practices, including model versioning, experiment tracking, and continuous integration/deployment (CI/CD) pipelines.</p></li><li><p style=\"min-height:1.5em\">Passion for advancing the state-of-the-art in reasoning and democratizing access to AI capabilities for researchers, developers, and businesses worldwide.</p></li><li><p style=\"min-height:1.5em\">If you're not familiar with these, but feel like that you can contribute to our mission and you're a high-energy person, get familiar with these resources (<a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://a.co/d/frW8MHY\">here</a>, <a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://a.co/d/4WRhR0Y\">here</a> and <a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://github.com/stas00/ml-engineering/tree/master\">here</a>) and please reach out!</p></li></ul><h2><strong>Benefits &amp; Perks</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation assistance for international candidates.</p></li><li><p style=\"min-height:1.5em\">Quarterly team off-sites, hackathons, conferences and learning opportunities.</p></li><li><p style=\"min-height:1.5em\">Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nRESPONSIBILITIES\n\n - Lead and participate in novel research to build a massive scale synthetic data generation pipeline and orchestration solution\n\n - Optimize the performance, cost, and resource utilization of AI inference workloads by leveraging the most recent advances for compute & memory optimization techniques.\n\n - Contribute to the development of our open-source libraries and frameworks for synthetic data generation and distributed RL frameworks.\n\n - Publish research in top-tier AI conferences such as ICML & NeurIPS.\n\n - Distill highly technical project outcomes in layman approachable technical blogs to our customers and developers.\n\n - Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, synthetic data gen research and proactively identify opportunities to enhance our platform's capabilities and user experience.\n\n\nREQUIREMENTS\n\n - Strong background in AI/ML engineering, with extensive experience in designing and implementing end-to-end pipelines for the inference or training of large-scale AI models.\n\n - Deep expertise in distributed inference techniques and frameworks (e.g. vllm, sglang) for optimizing the performance and scalability of AI workloads.\n\n - Solid understanding of MLOps best practices, including model versioning, experiment tracking, and continuous integration/deployment (CI/CD) pipelines.\n\n - Passion for advancing the state-of-the-art in reasoning and democratizing access to AI capabilities for researchers, developers, and businesses worldwide.\n\n - If you're not familiar with these, but feel like that you can contribute to our mission and you're a high-energy person, get familiar with these resources (here https://a.co/d/frW8MHY, here https://a.co/d/4WRhR0Y and here https://github.com/stas00/ml-engineering/tree/master) and please reach out!\n\n\nBENEFITS & PERKS\n\n - Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.\n\n - Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.\n\n - Visa sponsorship and relocation assistance for international candidates.\n\n - Quarterly team off-sites, hackathons, conferences and learning opportunities.\n\n - Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.\n\n\n\nIf you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you."},{"id":"c074bdd9-bee2-4ee9-ae03-aa8f7537682c","title":"Member of Technical Staff - Full Stack Software Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:45:08.431+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/c074bdd9-bee2-4ee9-ae03-aa8f7537682c","applyUrl":"https://jobs.ashbyhq.com/primeintellect/c074bdd9-bee2-4ee9-ae03-aa8f7537682c/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2>Role Impact</h2><p style=\"min-height:1.5em\">This is a generalist software engineering role focused on building the product surface of Prime Intellect - the developer-facing platform, APIs, and services that researchers and engineers around the world use to train and deploy frontier models. You'll own features end-to-end, from design through deployment and monitoring, and ship at the pace of an early-stage company tackling one of the most important problems in AI. </p><p style=\"min-height:1.5em\"></p><h2>Core Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build intuitive web interfaces for AI workload management and monitoring</p></li><li><p style=\"min-height:1.5em\">Develop REST APIs and backend services in Python</p></li><li><p style=\"min-height:1.5em\">Own features end-to-end, from design through deployment and operation</p></li><li><p style=\"min-height:1.5em\">Create real-time monitoring and debugging tools for users of the platform</p></li><li><p style=\"min-height:1.5em\">Implement user-facing features for resource management and job control</p></li><li><p style=\"min-height:1.5em\">Deploy and operate services on cloud infrastructure</p></li><li><p style=\"min-height:1.5em\">Contribute to internal tooling, automation, and developer experience improvements </p><p style=\"min-height:1.5em\"></p></li></ul><h2>Technical Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong Python backend development (FastAPI, async)</p></li><li><p style=\"min-height:1.5em\">Modern frontend development (TypeScript, React/Next.js, Tailwind)</p></li><li><p style=\"min-height:1.5em\">Experience building developer tools, dashboards, or platform products</p></li><li><p style=\"min-height:1.5em\">RESTful API design and implementation</p></li><li><p style=\"min-height:1.5em\">Comfortable working with cloud platforms (GCP a plus) and containerized deployments</p></li><li><p style=\"min-height:1.5em\">A bias toward shipping, ownership of production code, and pragmatic engineering judgment</p></li><li><p style=\"min-height:1.5em\">Infrastructure automation experience (Ansible, Terraform, Kubernetes)</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Interest in or exposure to ML/AI workloads</p></li><li><p style=\"min-height:1.5em\">WebSocket / real-time systems experience</p></li><li><p style=\"min-height:1.5em\">Open-source contributions</p></li><li><p style=\"min-height:1.5em\">Observability tooling (Prometheus, Grafana)</p></li><li><p style=\"min-height:1.5em\">Prior experience at an early-stage startup</p><p style=\"min-height:1.5em\"></p></li></ul><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation range of $150–300k with significant equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangement (remote or San Francisco office)</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">Opportunity to shape the future of open AI development </p><p style=\"min-height:1.5em\"></p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.</p><p style=\"min-height:1.5em\">We value potential over perfection - if you're a strong generalist engineer who is passionate about democratizing AI development, we want to talk to you.</p><p style=\"min-height:1.5em\">Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nROLE IMPACT\n\nThis is a generalist software engineering role focused on building the product surface of Prime Intellect - the developer-facing platform, APIs, and services that researchers and engineers around the world use to train and deploy frontier models. You'll own features end-to-end, from design through deployment and monitoring, and ship at the pace of an early-stage company tackling one of the most important problems in AI. \n\n\n\n\nCORE RESPONSIBILITIES\n\n - Build intuitive web interfaces for AI workload management and monitoring\n\n - Develop REST APIs and backend services in Python\n\n - Own features end-to-end, from design through deployment and operation\n\n - Create real-time monitoring and debugging tools for users of the platform\n\n - Implement user-facing features for resource management and job control\n\n - Deploy and operate services on cloud infrastructure\n\n - Contribute to internal tooling, automation, and developer experience improvements \n   \n   \n\n\nTECHNICAL REQUIREMENTS\n\n - Strong Python backend development (FastAPI, async)\n\n - Modern frontend development (TypeScript, React/Next.js, Tailwind)\n\n - Experience building developer tools, dashboards, or platform products\n\n - RESTful API design and implementation\n\n - Comfortable working with cloud platforms (GCP a plus) and containerized deployments\n\n - A bias toward shipping, ownership of production code, and pragmatic engineering judgment\n\n - Infrastructure automation experience (Ansible, Terraform, Kubernetes)\n\n\n\n\nNICE TO HAVE\n\n - Interest in or exposure to ML/AI workloads\n\n - WebSocket / real-time systems experience\n\n - Open-source contributions\n\n - Observability tooling (Prometheus, Grafana)\n\n - Prior experience at an early-stage startup\n   \n   \n\n\nWHAT WE OFFER\n\n - Cash compensation range of $150–300k with significant equity incentives\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n - Opportunity to shape the future of open AI development \n   \n   \n\n\nGROWTH OPPORTUNITY\n\nYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.\n\nWe value potential over perfection - if you're a strong generalist engineer who is passionate about democratizing AI development, we want to talk to you.\n\nReady to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone."},{"id":"b9343f5d-326d-4b01-b6a7-acf56cffe3ac","title":"Open Application for Unconventional Talent","department":"Others","team":"Others","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:43:13.470+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/b9343f5d-326d-4b01-b6a7-acf56cffe3ac","applyUrl":"https://jobs.ashbyhq.com/primeintellect/b9343f5d-326d-4b01-b6a7-acf56cffe3ac/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">If you’ve built complex technical systems, contributed meaningfully to open-source projects, or mastered multiple domains, we want to hear from you. Whether your expertise is in AI, distributed computing, cryptography, systems programming, or something unexpected, what matters is your ability to learn fast, think rigorously, and execute.</p><p style=\"min-height:1.5em\">Tell us what excites you about PrimeIntellect, something impressive that that you’ve built, and how you’d accelerate open and decentralized AGI.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nIf you’ve built complex technical systems, contributed meaningfully to open-source projects, or mastered multiple domains, we want to hear from you. Whether your expertise is in AI, distributed computing, cryptography, systems programming, or something unexpected, what matters is your ability to learn fast, think rigorously, and execute.\n\nTell us what excites you about PrimeIntellect, something impressive that that you’ve built, and how you’d accelerate open and decentralized AGI."},{"id":"6d77793a-ee30-41ea-9e28-1f3f3eb9ceb9","title":"Member of Technical Staff - Compute Platform","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:44:57.707+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/6d77793a-ee30-41ea-9e28-1f3f3eb9ceb9","applyUrl":"https://jobs.ashbyhq.com/primeintellect/6d77793a-ee30-41ea-9e28-1f3f3eb9ceb9/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h1><strong>Core Technical Responsibilities</strong></h1><p style=\"min-height:1.5em\">This hybrid role spans across our AI platform software engineering and infrastructure. You'll be instrumental in:</p><h2></h2><h2><strong>Platform Development</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build intuitive web interfaces for AI workload management and monitoring</p></li><li><p style=\"min-height:1.5em\">Develop REST APIs and backend services in Python</p></li><li><p style=\"min-height:1.5em\">Create real-time monitoring and debugging tools</p></li><li><p style=\"min-height:1.5em\">Implement user-facing features for resource management and job control<br /></p></li></ul><h2><strong>Infrastructure Development, Automation &amp; Reliability</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and implement distributed training infrastructure in Rust</p></li><li><p style=\"min-height:1.5em\">Build high-performance networking and coordination components</p></li><li><p style=\"min-height:1.5em\">Create infrastructure automation pipelines with Ansible</p></li><li><p style=\"min-height:1.5em\">Manage cloud resources and container orchestration</p></li><li><p style=\"min-height:1.5em\">Implement scheduling systems for heterogeneous hardware (CPU, GPU, TPU)</p></li></ul><p style=\"min-height:1.5em\"></p><h2><strong>Backend &amp; Feature Development</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>New Feature Engineering:</strong> Collaborate with the engineering team to design and implement backend features.</p></li><li><p style=\"min-height:1.5em\"><strong>API and Service Development:</strong> Enhance our platform’s REST APIs and backend services to support new capabilities and improve overall performance.</p></li><li><p style=\"min-height:1.5em\"><strong>System Integration:</strong> Ensure seamless integration of new features into our existing infrastructure, maintaining high reliability and security standards.</p><p style=\"min-height:1.5em\"></p></li></ul><p style=\"min-height:1.5em\"><strong>Development &amp; Infrastructure Skills</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Backend Engineering:</strong> Proficiency in Python for developing automation scripts, REST APIs, and backend support tools.</p></li><li><p style=\"min-height:1.5em\"><strong>Container &amp; Cloud Technologies:</strong> Hands-on experience with Kubernetes and cloud platforms (GCP preferred).</p></li></ul><p style=\"min-height:1.5em\"></p><h2><strong><br />Technical Requirements</strong></h2><p style=\"min-height:1.5em\"><strong>Platform Skills</strong></p><p style=\"min-height:1.5em\">- Strong Python backend development (FastAPI, async)</p><p style=\"min-height:1.5em\">- Modern frontend development (TypeScript, React/Next.js, Tailwind)</p><p style=\"min-height:1.5em\">- Experience building developer tools and dashboards</p><p style=\"min-height:1.5em\">- RESTful API design and implementation</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Infrastructure Skills</strong></p><p style=\"min-height:1.5em\">- Systems programming experience with Rust</p><p style=\"min-height:1.5em\">- Infrastructure automation (Ansible, Terraform)</p><p style=\"min-height:1.5em\">- Container orchestration (Kubernetes)</p><p style=\"min-height:1.5em\">- Cloud platform expertise (GCP preferred)</p><p style=\"min-height:1.5em\">- Observability tools (Prometheus, Grafana)</p><p style=\"min-height:1.5em\"></p><h2><strong>Nice to Have</strong></h2><p style=\"min-height:1.5em\">- Experience with GPU computing and ML infrastructure</p><p style=\"min-height:1.5em\">- Knowledge of AI/ML model architecture and training</p><p style=\"min-height:1.5em\">- High-performance networking implementation</p><p style=\"min-height:1.5em\">- Open-source infrastructure contributions</p><p style=\"min-height:1.5em\">- WebSocket/real-time systems experience</p><p style=\"min-height:1.5em\"></p><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions. </p><p style=\"min-height:1.5em\">We value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\nThis hybrid role spans across our AI platform software engineering and infrastructure. You'll be instrumental in:\n\n\n\n\n\nPLATFORM DEVELOPMENT\n\n - Build intuitive web interfaces for AI workload management and monitoring\n\n - Develop REST APIs and backend services in Python\n\n - Create real-time monitoring and debugging tools\n\n - Implement user-facing features for resource management and job control\n   \n\n\nINFRASTRUCTURE DEVELOPMENT, AUTOMATION & RELIABILITY\n\n - Design and implement distributed training infrastructure in Rust\n\n - Build high-performance networking and coordination components\n\n - Create infrastructure automation pipelines with Ansible\n\n - Manage cloud resources and container orchestration\n\n - Implement scheduling systems for heterogeneous hardware (CPU, GPU, TPU)\n\n\n\n\nBACKEND & FEATURE DEVELOPMENT\n\n - New Feature Engineering: Collaborate with the engineering team to design and implement backend features.\n\n - API and Service Development: Enhance our platform’s REST APIs and backend services to support new capabilities and improve overall performance.\n\n - System Integration: Ensure seamless integration of new features into our existing infrastructure, maintaining high reliability and security standards.\n   \n   \n\nDevelopment & Infrastructure Skills\n\n - Backend Engineering: Proficiency in Python for developing automation scripts, REST APIs, and backend support tools.\n\n - Container & Cloud Technologies: Hands-on experience with Kubernetes and cloud platforms (GCP preferred).\n\n\n\n\n\nTECHNICAL REQUIREMENTS\n\nPlatform Skills\n\n- Strong Python backend development (FastAPI, async)\n\n- Modern frontend development (TypeScript, React/Next.js, Tailwind)\n\n- Experience building developer tools and dashboards\n\n- RESTful API design and implementation\n\n\n\nInfrastructure Skills\n\n- Systems programming experience with Rust\n\n- Infrastructure automation (Ansible, Terraform)\n\n- Container orchestration (Kubernetes)\n\n- Cloud platform expertise (GCP preferred)\n\n- Observability tools (Prometheus, Grafana)\n\n\n\n\nNICE TO HAVE\n\n- Experience with GPU computing and ML infrastructure\n\n- Knowledge of AI/ML model architecture and training\n\n- High-performance networking implementation\n\n- Open-source infrastructure contributions\n\n- WebSocket/real-time systems experience\n\n\n\n\nGROWTH OPPORTUNITY\n\nYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions. \n\nWe value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you."},{"id":"486b3511-7128-46f9-93a5-fc1d748d8852","title":"Internship","department":"Others","team":"Others","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:42:43.546+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/486b3511-7128-46f9-93a5-fc1d748d8852","applyUrl":"https://jobs.ashbyhq.com/primeintellect/486b3511-7128-46f9-93a5-fc1d748d8852/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">We’re looking for exceptional interns who’ve already built real systems, contributed to open-source, or gone deep across technical domains.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">If you thrive in open-ended, high-stakes problem spaces and want to push the limits of open, distributed AI, we want to hear from you. Whether your strength is in AI, systems, distributed compute, cryptography, or something unexpected, what matters is how fast you learn, how well you execute, and how deeply you think.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Tell us what excites you about PrimeIntellect, something impressive you’ve built, and how you’d accelerate decentralized AGI.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nWe’re looking for exceptional interns who’ve already built real systems, contributed to open-source, or gone deep across technical domains.\n\n\n\nIf you thrive in open-ended, high-stakes problem spaces and want to push the limits of open, distributed AI, we want to hear from you. Whether your strength is in AI, systems, distributed compute, cryptography, or something unexpected, what matters is how fast you learn, how well you execute, and how deeply you think.\n\n\n\nTell us what excites you about PrimeIntellect, something impressive you’ve built, and how you’d accelerate decentralized AGI."},{"id":"bbfe94a6-d1a8-47e9-86af-f117277cdacb","title":"Applied Research - Evals & Data","department":"Applied Research","team":"Applied Research","employmentType":"FullTime","location":"New York City, USA","secondaryLocations":[],"publishedAt":"2026-07-08T18:34:09.743+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":null,"jobUrl":"https://jobs.ashbyhq.com/primeintellect/bbfe94a6-d1a8-47e9-86af-f117277cdacb","applyUrl":"https://jobs.ashbyhq.com/primeintellect/bbfe94a6-d1a8-47e9-86af-f117277cdacb/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"><br /><strong>Role Impact</strong></p><p style=\"min-height:1.5em\">This is a customer facing role at the intersection of cutting-edge RL/post-training methods, applied data, and agent systems. You’ll have a direct impact on shaping how advanced models are aligned, evaluated, deployed, and used in the real world by:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Advancing Agent Capabilities:</strong> Designing and iterating on next-generation AI agents that tackle real workloads—workflow automation, reasoning-intensive tasks, and decision-making at scale. Working with applied data from real deployments to continuously refine policies, improve reasoning, and enhance reliability and safety.</p></li><li><p style=\"min-height:1.5em\"><strong>Building Robust Infrastructure:</strong> Developing the distributed systems, evaluation pipelines, and coordination frameworks that enable these agents to operate reliably, efficiently, and at massive scale. Building data capture, processing, and versioning workflows for feedback, model traces, and reward signals.</p></li><li><p style=\"min-height:1.5em\"><strong>Bridge Between Customers &amp; Research:</strong> Translating customer needs and insights from applied data into clear technical requirements that guide product and research priorities. Collaborating closely with RL and eval teams to ensure real-world signals inform model alignment and reward shaping.</p></li><li><p style=\"min-height:1.5em\"><strong>Prototype in the Field:</strong> Rapidly designing and deploying agents, evals, and harnesses alongside customers to validate solutions. Using applied evaluation data to iterate on model performance and discover new capabilities.</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>Customer-Facing Engineering</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Work side-by-side with customers to deeply understand workflows, data sources, and bottlenecks.</p></li><li><p style=\"min-height:1.5em\">Prototype agents, data pipelines, and eval harnesses tailored to real use cases, then hand off hardened systems to core teams.</p></li><li><p style=\"min-height:1.5em\">Translate customer insights and evaluation results into roadmap and research direction.</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>Post-training &amp; Reinforcement Learning</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and implement novel RL and post-training methods (RLHF, RLVR, GRPO, etc.) to align large models with domain-specific tasks.</p></li><li><p style=\"min-height:1.5em\">Build evaluation harnesses and verifiers to measure reasoning, robustness, and agentic behavior in real-world workflows.</p></li><li><p style=\"min-height:1.5em\">Integrate applied data collection and analytics into the post-training process to surface regressions, emergent skills, and alignment opportunities.</p></li><li><p style=\"min-height:1.5em\">Prototype multi-agent and memory-augmented systems to expand capabilities for customer-facing solutions.</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>Agent Development &amp; Infrastructure</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Rapidly prototype and iterate on AI agents for automation, workflow orchestration, and decision-making.</p></li><li><p style=\"min-height:1.5em\">Extend and integrate with agent frameworks to support evolving feature requests and performance requirements.</p></li><li><p style=\"min-height:1.5em\">Architect and maintain distributed training and inference pipelines, ensuring scalability and cost efficiency.</p></li><li><p style=\"min-height:1.5em\">Develop observability and monitoring (Prometheus, Grafana, tracing) to ensure reliability and performance in production deployments.</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>Requirements</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong background in machine learning engineering, with experience in post-training, RL, or large-scale model alignment.</p></li><li><p style=\"min-height:1.5em\">Experience with applied data workflows and evaluation frameworks for large models or agents (e.g., SWE-Bench, HELM, EvalFlow, internal eval pipelines).</p></li><li><p style=\"min-height:1.5em\">Deep expertise in distributed training/inference frameworks (e.g., vLLM, sglang, Ray, Accelerate).</p></li><li><p style=\"min-height:1.5em\">Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).</p></li><li><p style=\"min-height:1.5em\">Track record of research contributions (publications, open-source contributions, benchmarks) in ML/RL.</p></li><li><p style=\"min-height:1.5em\">Passion for advancing the state-of-the-art in reasoning, measurement, and building practical, agentic AI systems.</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>What We Offer</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150-300k + equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible Work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa Sponsorship &amp; relocation support</p></li><li><p style=\"min-height:1.5em\">Professional Development budget</p></li><li><p style=\"min-height:1.5em\">Team Off-sites &amp; conference attendance</p></li></ul><p style=\"min-height:1.5em\"><br /><strong>Growth Opportunity</strong></p><p style=\"min-height:1.5em\">You’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Shape the evolution of agent-driven, data-informed solutions—from research breakthroughs to production systems used by real customers.</p></li><li><p style=\"min-height:1.5em\">Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL, evaluation, and post-training.</p></li><li><p style=\"min-height:1.5em\">Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.</p></li></ul><p style=\"min-height:1.5em\">If you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.</p><p style=\"min-height:1.5em\">Ready to build the open superintelligence infrastructure of tomorrow?<br />Apply now to help us make powerful, open AGI accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nRole Impact\n\nThis is a customer facing role at the intersection of cutting-edge RL/post-training methods, applied data, and agent systems. You’ll have a direct impact on shaping how advanced models are aligned, evaluated, deployed, and used in the real world by:\n\n - Advancing Agent Capabilities: Designing and iterating on next-generation AI agents that tackle real workloads—workflow automation, reasoning-intensive tasks, and decision-making at scale. Working with applied data from real deployments to continuously refine policies, improve reasoning, and enhance reliability and safety.\n\n - Building Robust Infrastructure: Developing the distributed systems, evaluation pipelines, and coordination frameworks that enable these agents to operate reliably, efficiently, and at massive scale. Building data capture, processing, and versioning workflows for feedback, model traces, and reward signals.\n\n - Bridge Between Customers & Research: Translating customer needs and insights from applied data into clear technical requirements that guide product and research priorities. Collaborating closely with RL and eval teams to ensure real-world signals inform model alignment and reward shaping.\n\n - Prototype in the Field: Rapidly designing and deploying agents, evals, and harnesses alongside customers to validate solutions. Using applied evaluation data to iterate on model performance and discover new capabilities.\n\n\nCustomer-Facing Engineering\n\n - Work side-by-side with customers to deeply understand workflows, data sources, and bottlenecks.\n\n - Prototype agents, data pipelines, and eval harnesses tailored to real use cases, then hand off hardened systems to core teams.\n\n - Translate customer insights and evaluation results into roadmap and research direction.\n\n\nPost-training & Reinforcement Learning\n\n - Design and implement novel RL and post-training methods (RLHF, RLVR, GRPO, etc.) to align large models with domain-specific tasks.\n\n - Build evaluation harnesses and verifiers to measure reasoning, robustness, and agentic behavior in real-world workflows.\n\n - Integrate applied data collection and analytics into the post-training process to surface regressions, emergent skills, and alignment opportunities.\n\n - Prototype multi-agent and memory-augmented systems to expand capabilities for customer-facing solutions.\n\n\nAgent Development & Infrastructure\n\n - Rapidly prototype and iterate on AI agents for automation, workflow orchestration, and decision-making.\n\n - Extend and integrate with agent frameworks to support evolving feature requests and performance requirements.\n\n - Architect and maintain distributed training and inference pipelines, ensuring scalability and cost efficiency.\n\n - Develop observability and monitoring (Prometheus, Grafana, tracing) to ensure reliability and performance in production deployments.\n\n\nRequirements\n\n - Strong background in machine learning engineering, with experience in post-training, RL, or large-scale model alignment.\n\n - Experience with applied data workflows and evaluation frameworks for large models or agents (e.g., SWE-Bench, HELM, EvalFlow, internal eval pipelines).\n\n - Deep expertise in distributed training/inference frameworks (e.g., vLLM, sglang, Ray, Accelerate).\n\n - Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).\n\n - Track record of research contributions (publications, open-source contributions, benchmarks) in ML/RL.\n\n - Passion for advancing the state-of-the-art in reasoning, measurement, and building practical, agentic AI systems.\n\n\nWhat We Offer\n\n - Cash Compensation Range of $150-300k + equity incentives\n\n - Flexible Work (remote or San Francisco)\n\n - Visa Sponsorship & relocation support\n\n - Professional Development budget\n\n - Team Off-sites & conference attendance\n\n\nGrowth Opportunity\n\nYou’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:\n\n - Shape the evolution of agent-driven, data-informed solutions—from research breakthroughs to production systems used by real customers.\n\n - Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL, evaluation, and post-training.\n\n - Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.\n\nIf you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.\n\nReady to build the open superintelligence infrastructure of tomorrow?\nApply now to help us make powerful, open AGI accessible to everyone."},{"id":"abfa70f7-a6f1-44d2-a6c1-560e1c8477d4","title":"Member of Technical Staff - Inference","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Remote","secondaryLocations":[{"location":"San Francisco","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}}}],"publishedAt":"2026-07-08T18:45:28.420+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressCountry":"United States"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/abfa70f7-a6f1-44d2-a6c1-560e1c8477d4","applyUrl":"https://jobs.ashbyhq.com/primeintellect/abfa70f7-a6f1-44d2-a6c1-560e1c8477d4/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><strong>Role Impact</strong></h2><p style=\"min-height:1.5em\">This is a hybrid position spanning cloud LLM serving, LLM inference optimization and RL systems. You will be working on advancing our ability to evaluate and serve models trained with our RL Lab at scale. The two key areas are:</p><ol style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Building the infrastructure to serve LLMs efficiently at scale.</p></li><li><p style=\"min-height:1.5em\">Optimization and integration of inference systems into our RL training stack.</p></li></ol><p style=\"min-height:1.5em\"></p><h2><strong>Core Technical Responsibilities</strong></h2><p style=\"min-height:1.5em\"><strong>LLM Serving</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Multi‑tenant LLM Serving:</strong> Build a multi-tenant LLM serving platform that operates across our cloud GPU fleets.</p></li><li><p style=\"min-height:1.5em\"><strong>GPU‑Aware Scheduling:</strong> Design placement and scheduling algorithms for heterogeneous accelerators.</p></li><li><p style=\"min-height:1.5em\"><strong>Resilience &amp; Failover:</strong> Implement multi‑region/zone failover and traffic shifting for resilience and cost control.</p></li><li><p style=\"min-height:1.5em\"><strong>Autoscaling &amp; Routing:</strong> Build autoscaling, routing, and load balancing to meet throughput/latency SLOs.</p></li><li><p style=\"min-height:1.5em\"><strong>Model Distribution:</strong> Optimize model distribution and cold-start times across clusters.</p></li></ul><p style=\"min-height:1.5em\"><strong>Inference Optimization &amp; Performance</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Framework Development:</strong> Integrate and contribute to LLM inference frameworks such as vLLM, SGLang, TensorRT‑LLM.</p></li><li><p style=\"min-height:1.5em\"><strong>Parallelism and Configuration Tuning:</strong> Optimize configurations for tensor/pipeline/expert parallelism, prefix caching, memory management and other axes for maximum performance.</p></li><li><p style=\"min-height:1.5em\"><strong>End‑to‑End Performance:</strong> Profile kernels, memory bandwidth and transport; apply techniques such as quantization and speculative decoding.</p></li><li><p style=\"min-height:1.5em\"><strong>Perf Suites:</strong> Develop reproducible performance suites (latency, throughput, context length, batch size, precision).</p></li><li><p style=\"min-height:1.5em\"><strong>RL Integration:</strong> Embed and optimize distributed inference within our RL stack.</p></li></ul><p style=\"min-height:1.5em\"><strong>Platform &amp; Tooling</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>CI/CD:</strong> Establish CI/CD with artifact promotion, performance gates, and reproducible builds.</p></li><li><p style=\"min-height:1.5em\"><strong>Observability:</strong> Build metrics, logs, tracing; structured incident response and SLO management.</p></li><li><p style=\"min-height:1.5em\"><strong>Docs &amp; Collaboration:</strong> Document architectures, playbooks, and API contracts; mentor and collaborate cross‑functionally.</p></li></ul><h2>Technical Requirements</h2><p style=\"min-height:1.5em\"><strong>Required Experience</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Building ML Systems at Scale:</strong> 3+ years building and running large‑scale ML/LLM services with clear latency/availability SLOs.</p></li><li><p style=\"min-height:1.5em\"><strong>Inference Backends:</strong> Hands‑on with at least one of vLLM, SGLang, TensorRT‑LLM.</p></li><li><p style=\"min-height:1.5em\"><strong>Distributed Serving Infra:</strong> Familiarity with distributed and disaggregated serving infrastructure such as NVIDIA Dynamo.</p></li><li><p style=\"min-height:1.5em\"><strong>Inference Internals:</strong> Deep understanding of prefill vs. decode, KV‑cache behavior, batching, sampling, speculative decoding, parallelism strategies.</p></li><li><p style=\"min-height:1.5em\"><strong>Full‑Stack Debugging:</strong> Comfortable debugging CUDA/NCCL, drivers/kernels, containers, service mesh/networking, and storage, owning incidents end‑to‑end.</p></li></ul><p style=\"min-height:1.5em\"><strong>Infrastructure Skills</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Python:</strong> Systems tooling and backend services.</p></li><li><p style=\"min-height:1.5em\"><strong>PyTorch:</strong> LLM Inference engine development and integration, deployment readiness.</p></li><li><p style=\"min-height:1.5em\"><strong>Cloud &amp; Automation:</strong> AWS/GCP service experience, cloud deployment patterns.</p></li><li><p style=\"min-height:1.5em\"><strong>Kubernetes:</strong> Running infrastructure at scale with containers on Kubernetes.</p></li><li><p style=\"min-height:1.5em\"><strong>GPU &amp; Networking:</strong> Architecture, CUDA runtime, NCCL, InfiniBand; GPU‑aware bin‑packing and scheduling across heterogeneous fleets.</p></li></ul><p style=\"min-height:1.5em\"><strong>Nice to Have</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Kernel‑Level Optimization:</strong> Familiarity with CUDA/Triton kernel development; Nsight Systems/Compute profiling.</p></li><li><p style=\"min-height:1.5em\"><strong>Systems Performance Languages:</strong> Rust, C++<strong>.</strong></p></li><li><p style=\"min-height:1.5em\"><strong>Data &amp; Observability:</strong> Kafka/PubSub, Redis, gRPC/Protobuf; Prometheus/Grafana, OpenTelemetry; reliability patterns.</p></li><li><p style=\"min-height:1.5em\"><strong>Infra &amp; Config Automation</strong>: Terraform/Ansible, infrastructure-as-code, reproducible environments</p></li><li><p style=\"min-height:1.5em\"><strong>Open Source:</strong> Contributions to serving, inference, or RL infrastructure projects.</p></li></ul><h2><strong>What We Offer</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Cash Compensation Range </strong>of $150-300k<strong> </strong>with significant equity incentives</p></li><li><p style=\"min-height:1.5em\"><strong>Flexible work</strong> arrangement (remote or San Francisco office)</p></li><li><p style=\"min-height:1.5em\"><strong>Full visa sponsorship</strong> and relocation support</p></li><li><p style=\"min-height:1.5em\"><strong>Professional development</strong> budget</p></li><li><p style=\"min-height:1.5em\"><strong>Regular team off-sites</strong> and conference attendance</p></li><li><p style=\"min-height:1.5em\"><strong>Opportunity to shape decentralized AI and RL</strong> at Prime Intellect</p></li></ul><h2><strong>Growth Opportunity</strong></h2><p style=\"min-height:1.5em\">You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.</p><p style=\"min-height:1.5em\">We value potential over perfection. If you're passionate about democratizing AI development, we want to talk to you.</p><p style=\"min-height:1.5em\"><strong>Ready to help shape the future of AI?</strong> Apply now and join us in our mission to make powerful AI models accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nROLE IMPACT\n\nThis is a hybrid position spanning cloud LLM serving, LLM inference optimization and RL systems. You will be working on advancing our ability to evaluate and serve models trained with our RL Lab at scale. The two key areas are:\n\n 1. Building the infrastructure to serve LLMs efficiently at scale.\n\n 2. Optimization and integration of inference systems into our RL training stack.\n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\nLLM Serving\n\n - Multi‑tenant LLM Serving: Build a multi-tenant LLM serving platform that operates across our cloud GPU fleets.\n\n - GPU‑Aware Scheduling: Design placement and scheduling algorithms for heterogeneous accelerators.\n\n - Resilience & Failover: Implement multi‑region/zone failover and traffic shifting for resilience and cost control.\n\n - Autoscaling & Routing: Build autoscaling, routing, and load balancing to meet throughput/latency SLOs.\n\n - Model Distribution: Optimize model distribution and cold-start times across clusters.\n\nInference Optimization & Performance\n\n - Framework Development: Integrate and contribute to LLM inference frameworks such as vLLM, SGLang, TensorRT‑LLM.\n\n - Parallelism and Configuration Tuning: Optimize configurations for tensor/pipeline/expert parallelism, prefix caching, memory management and other axes for maximum performance.\n\n - End‑to‑End Performance: Profile kernels, memory bandwidth and transport; apply techniques such as quantization and speculative decoding.\n\n - Perf Suites: Develop reproducible performance suites (latency, throughput, context length, batch size, precision).\n\n - RL Integration: Embed and optimize distributed inference within our RL stack.\n\nPlatform & Tooling\n\n - CI/CD: Establish CI/CD with artifact promotion, performance gates, and reproducible builds.\n\n - Observability: Build metrics, logs, tracing; structured incident response and SLO management.\n\n - Docs & Collaboration: Document architectures, playbooks, and API contracts; mentor and collaborate cross‑functionally.\n\n\nTECHNICAL REQUIREMENTS\n\nRequired Experience\n\n - Building ML Systems at Scale: 3+ years building and running large‑scale ML/LLM services with clear latency/availability SLOs.\n\n - Inference Backends: Hands‑on with at least one of vLLM, SGLang, TensorRT‑LLM.\n\n - Distributed Serving Infra: Familiarity with distributed and disaggregated serving infrastructure such as NVIDIA Dynamo.\n\n - Inference Internals: Deep understanding of prefill vs. decode, KV‑cache behavior, batching, sampling, speculative decoding, parallelism strategies.\n\n - Full‑Stack Debugging: Comfortable debugging CUDA/NCCL, drivers/kernels, containers, service mesh/networking, and storage, owning incidents end‑to‑end.\n\nInfrastructure Skills\n\n - Python: Systems tooling and backend services.\n\n - PyTorch: LLM Inference engine development and integration, deployment readiness.\n\n - Cloud & Automation: AWS/GCP service experience, cloud deployment patterns.\n\n - Kubernetes: Running infrastructure at scale with containers on Kubernetes.\n\n - GPU & Networking: Architecture, CUDA runtime, NCCL, InfiniBand; GPU‑aware bin‑packing and scheduling across heterogeneous fleets.\n\nNice to Have\n\n - Kernel‑Level Optimization: Familiarity with CUDA/Triton kernel development; Nsight Systems/Compute profiling.\n\n - Systems Performance Languages: Rust, C++.\n\n - Data & Observability: Kafka/PubSub, Redis, gRPC/Protobuf; Prometheus/Grafana, OpenTelemetry; reliability patterns.\n\n - Infra & Config Automation: Terraform/Ansible, infrastructure-as-code, reproducible environments\n\n - Open Source: Contributions to serving, inference, or RL infrastructure projects.\n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $150-300k with significant equity incentives\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget\n\n - Regular team off-sites and conference attendance\n\n - Opportunity to shape decentralized AI and RL at Prime Intellect\n\n\nGROWTH OPPORTUNITY\n\nYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.\n\nWe value potential over perfection. If you're passionate about democratizing AI development, we want to talk to you.\n\nReady to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone."},{"id":"297d925e-5a42-40bd-b02f-5c928d226f18","title":"Member of Technical Staff - GPU Infrastructure","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:45:18.934+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/297d925e-5a42-40bd-b02f-5c928d226f18","applyUrl":"https://jobs.ashbyhq.com/primeintellect/297d925e-5a42-40bd-b02f-5c928d226f18/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Core Technical Responsibilities</strong></p><p style=\"min-height:1.5em\">This customer-facing role combines deep technical expertise with hands-on implementation. You'll be instrumental in:</p><p style=\"min-height:1.5em\"><strong>Customer Architecture &amp; Design</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Partner with clients to understand workload requirements and design optimal GPU cluster architectures</p></li><li><p style=\"min-height:1.5em\">Create technical proposals and capacity planning for clusters ranging from 100 to 10,000+ GPUs</p></li><li><p style=\"min-height:1.5em\">Develop deployment strategies for LLM training, inference, and HPC workloads</p></li><li><p style=\"min-height:1.5em\">Present architectural recommendations to technical and executive stakeholders</p></li></ul><p style=\"min-height:1.5em\"><strong>Infrastructure Deployment &amp; Optimization</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Deploy and configure orchestration systems including SLURM and Kubernetes for distributed workloads</p></li><li><p style=\"min-height:1.5em\">Implement high-performance networking with InfiniBand, RoCE, and NVLink interconnects</p></li><li><p style=\"min-height:1.5em\">Optimize GPU utilization, memory management, and inter-node communication</p></li><li><p style=\"min-height:1.5em\">Configure parallel filesystems (Lustre, BeeGFS, GPFS) for optimal I/O performance</p></li><li><p style=\"min-height:1.5em\">Tune system performance from kernel parameters to CUDA configurations</p></li></ul><p style=\"min-height:1.5em\"><strong>Production Operations &amp; Support</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Serve as primary technical escalation point for customer infrastructure issues</p></li><li><p style=\"min-height:1.5em\">Diagnose and resolve complex problems across the full stack - hardware, drivers, networking, and software</p></li><li><p style=\"min-height:1.5em\">Implement monitoring, alerting, and automated remediation systems</p></li><li><p style=\"min-height:1.5em\">Provide 24/7 on-call support for critical customer deployments</p></li><li><p style=\"min-height:1.5em\">Create runbooks and documentation for customer operations teams</p></li></ul><p style=\"min-height:1.5em\"><strong>Technical Requirements</strong></p><p style=\"min-height:1.5em\"><strong>Required Experience</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3+ years hands-on experience with GPU clusters and HPC environments</p></li><li><p style=\"min-height:1.5em\">Deep expertise with SLURM and Kubernetes in production GPU settings</p></li><li><p style=\"min-height:1.5em\">Proven experience with InfiniBand configuration and troubleshooting</p></li><li><p style=\"min-height:1.5em\">Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack</p></li><li><p style=\"min-height:1.5em\">Experience with infrastructure automation tools (Ansible, Terraform)</p></li><li><p style=\"min-height:1.5em\">Proficiency in Python, Bash, and systems programming</p></li><li><p style=\"min-height:1.5em\">Track record of customer-facing technical leadership</p></li></ul><p style=\"min-height:1.5em\"><strong>Infrastructure Skills</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">NVIDIA driver installation and troubleshooting (CUDA, Fabric Manager, DCGM)</p></li><li><p style=\"min-height:1.5em\">Container runtime configuration for GPUs (Docker, Containerd, Enroot)</p></li><li><p style=\"min-height:1.5em\">Linux kernel tuning and performance optimization</p></li><li><p style=\"min-height:1.5em\">Network topology design for AI workloads</p></li><li><p style=\"min-height:1.5em\">Power and cooling requirements for high-density GPU deployments</p></li></ul><p style=\"min-height:1.5em\"><strong>Nice to Have</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with 1000+ GPU deployments</p></li><li><p style=\"min-height:1.5em\">NVIDIA DGX, HGX, or SuperPOD certification</p></li><li><p style=\"min-height:1.5em\">Distributed training frameworks (PyTorch FSDP, DeepSpeed, Megatron-LM)</p></li><li><p style=\"min-height:1.5em\">ML framework optimization and profiling</p></li><li><p style=\"min-height:1.5em\">Experience with AMD MI300 or Intel Gaudi accelerators</p></li><li><p style=\"min-height:1.5em\">Contributions to open-source HPC/AI infrastructure projects</p></li></ul><p style=\"min-height:1.5em\"><strong>Growth Opportunity</strong></p><p style=\"min-height:1.5em\">You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.</p><p style=\"min-height:1.5em\">We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and join us in our mission to democratize access to planetary scale computing.</p><p style=\"min-height:1.5em\"><strong>Compensation</strong></p><p style=\"min-height:1.5em\">Cash Compensation Range of $150-300k plus Equity Incentives</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nCore Technical Responsibilities\n\nThis customer-facing role combines deep technical expertise with hands-on implementation. You'll be instrumental in:\n\nCustomer Architecture & Design\n\n - Partner with clients to understand workload requirements and design optimal GPU cluster architectures\n\n - Create technical proposals and capacity planning for clusters ranging from 100 to 10,000+ GPUs\n\n - Develop deployment strategies for LLM training, inference, and HPC workloads\n\n - Present architectural recommendations to technical and executive stakeholders\n\nInfrastructure Deployment & Optimization\n\n - Deploy and configure orchestration systems including SLURM and Kubernetes for distributed workloads\n\n - Implement high-performance networking with InfiniBand, RoCE, and NVLink interconnects\n\n - Optimize GPU utilization, memory management, and inter-node communication\n\n - Configure parallel filesystems (Lustre, BeeGFS, GPFS) for optimal I/O performance\n\n - Tune system performance from kernel parameters to CUDA configurations\n\nProduction Operations & Support\n\n - Serve as primary technical escalation point for customer infrastructure issues\n\n - Diagnose and resolve complex problems across the full stack - hardware, drivers, networking, and software\n\n - Implement monitoring, alerting, and automated remediation systems\n\n - Provide 24/7 on-call support for critical customer deployments\n\n - Create runbooks and documentation for customer operations teams\n\nTechnical Requirements\n\nRequired Experience\n\n - 3+ years hands-on experience with GPU clusters and HPC environments\n\n - Deep expertise with SLURM and Kubernetes in production GPU settings\n\n - Proven experience with InfiniBand configuration and troubleshooting\n\n - Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack\n\n - Experience with infrastructure automation tools (Ansible, Terraform)\n\n - Proficiency in Python, Bash, and systems programming\n\n - Track record of customer-facing technical leadership\n\nInfrastructure Skills\n\n - NVIDIA driver installation and troubleshooting (CUDA, Fabric Manager, DCGM)\n\n - Container runtime configuration for GPUs (Docker, Containerd, Enroot)\n\n - Linux kernel tuning and performance optimization\n\n - Network topology design for AI workloads\n\n - Power and cooling requirements for high-density GPU deployments\n\nNice to Have\n\n - Experience with 1000+ GPU deployments\n\n - NVIDIA DGX, HGX, or SuperPOD certification\n\n - Distributed training frameworks (PyTorch FSDP, DeepSpeed, Megatron-LM)\n\n - ML framework optimization and profiling\n\n - Experience with AMD MI300 or Intel Gaudi accelerators\n\n - Contributions to open-source HPC/AI infrastructure projects\n\nGrowth Opportunity\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\nCompensation\n\nCash Compensation Range of $150-300k plus Equity Incentives"},{"id":"46d9d060-5f48-4491-848f-bafbeb3a4325","title":"Applied Research - RL & Agents","department":"Applied Research","team":"Applied Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:34:52.078+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/46d9d060-5f48-4491-848f-bafbeb3a4325","applyUrl":"https://jobs.ashbyhq.com/primeintellect/46d9d060-5f48-4491-848f-bafbeb3a4325/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2><br />Role Impact</h2><p style=\"min-height:1.5em\">This is a role at the intersection of cutting-edge RL/post-training methods and applied agent systems. You’ll have a direct impact on shaping how advanced models are aligned, deployed, and used in the real world by:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Advancing Agent Capabilities</strong>: Designing and iterating on next-generation AI agents that tackle real workloads—workflow automation, reasoning-intensive tasks, and decision-making at scale.</p></li><li><p style=\"min-height:1.5em\"><strong>Building Robust Infrastructure</strong>: Developing the systems and frameworks that enable these agents to operate reliably, efficiently, and at massive scale.</p></li><li><p style=\"min-height:1.5em\"><strong>Bridge Between Applications &amp; Research</strong>: Translate ambiguous objectives into clear technical requirements that guide product and research priorities.</p></li><li><p style=\"min-height:1.5em\"><strong>Prototype in the Field</strong>: Rapidly design and deploy agents, evals, and harnesses for real-world tasks to validate solutions.</p></li></ul><h3></h3><p style=\"min-height:1.5em\"><strong>Application-Driven Research &amp; Infrastructure</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Shape the direction and feature set for verifiers, the Environments Hub, training services, and other research platform offerings.</p></li><li><p style=\"min-height:1.5em\">Build high‑quality examples, reference implementations, and “recipes” that make it easy for others to extend the stack.</p></li><li><p style=\"min-height:1.5em\">Prototype agents and eval harnesses tailored to real-world use cases and external systems.</p></li><li><p style=\"min-height:1.5em\">Pair with technical end‑users (research teams, infra‑heavy customers, open‑source contributors) to design environments, evals, and verifiers that reflect real workloads.</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Post-training &amp; Reinforcement Learning</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and implement novel RL and post-training methods (RLHF, RLVR, GRPO, etc.) to align large models with domain-specific tasks.</p></li><li><p style=\"min-height:1.5em\">Build evaluations and harnesses and to measure reasoning, robustness, and agentic behavior in real-world workflows.</p></li><li><p style=\"min-height:1.5em\">Prototype multi-agent and memory-augmented systems to expand capabilities for downstream applications.</p></li><li><p style=\"min-height:1.5em\">Experiment with post-training recipes to optimize downstream performance.  </p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Agent Development &amp; Infrastructure</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Rapidly prototype and iterate on AI agents for automation, workflow orchestration, and decision-making.</p></li><li><p style=\"min-height:1.5em\">Extend and integrate with agent frameworks to support evolving feature requests and performance requirements.</p></li><li><p style=\"min-height:1.5em\">Architect and maintain distributed training/inference pipelines, ensuring scalability and cost efficiency.</p></li><li><p style=\"min-height:1.5em\">Develop observability and monitoring (Prometheus, Grafana, tracing) to ensure reliability and performance in production deployments.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong background in machine learning engineering, with experience in post-training, RL, or large-scale model alignment. </p></li><li><p style=\"min-height:1.5em\">Experience with agent frameworks and tooling (e.g. DSPy, LangGraph, MCP, Stagehand).</p></li><li><p style=\"min-height:1.5em\">Familiarity with distributed training/inference frameworks (e.g., vLLM, sglang, Accelerate, Ray, Torch).</p></li><li><p style=\"min-height:1.5em\">Track record of research contributions (publications, open-source contributions, benchmarks) in ML/RL.</p></li><li><p style=\"min-height:1.5em\">Passion for advancing the state-of-the-art in reasoning and building practical, agentic AI systems.</p></li><li><p style=\"min-height:1.5em\">Strong technical writing abilities (documentation, blogs, papers) and research taste.</p></li><li><p style=\"min-height:1.5em\">Eagerness to drive collaborations with external partners and engage with the broader open-source community.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Nice-to-Haves</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with web programming (React, TypeScript, Next.js).</p></li><li><p style=\"min-height:1.5em\">Experience running LLM evaluations and/or synthetic data generation.</p></li><li><p style=\"min-height:1.5em\">Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).<br /></p></li></ul><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Cash Compensation Range of $150-300k </strong>+ equity incentives</p></li><li><p style=\"min-height:1.5em\"><strong>Flexible Work</strong> (San Francisco or hybrid-remote)</p></li><li><p style=\"min-height:1.5em\"><strong>Visa Sponsorship</strong> &amp; relocation support</p></li><li><p style=\"min-height:1.5em\"><strong>Professional Development</strong> budget</p></li><li><p style=\"min-height:1.5em\"><strong>Team Off-sites</strong> &amp; conference attendance</p></li></ul><h2><br />Growth Opportunity</h2><p style=\"min-height:1.5em\">You’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Shape the evolution of agent-driven solutions—from research breakthroughs to production systems used by real customers.</p></li><li><p style=\"min-height:1.5em\">Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL and post-training.</p></li><li><p style=\"min-height:1.5em\">Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.</p></li></ul><p style=\"min-height:1.5em\">If you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Ready to build the open superintelligence infrastructure of tomorrow?</strong><br />Apply now to help us make powerful, open AGI accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nROLE IMPACT\n\nThis is a role at the intersection of cutting-edge RL/post-training methods and applied agent systems. You’ll have a direct impact on shaping how advanced models are aligned, deployed, and used in the real world by:\n\n - Advancing Agent Capabilities: Designing and iterating on next-generation AI agents that tackle real workloads—workflow automation, reasoning-intensive tasks, and decision-making at scale.\n\n - Building Robust Infrastructure: Developing the systems and frameworks that enable these agents to operate reliably, efficiently, and at massive scale.\n\n - Bridge Between Applications & Research: Translate ambiguous objectives into clear technical requirements that guide product and research priorities.\n\n - Prototype in the Field: Rapidly design and deploy agents, evals, and harnesses for real-world tasks to validate solutions.\n\n\n\n\nApplication-Driven Research & Infrastructure\n\n - Shape the direction and feature set for verifiers, the Environments Hub, training services, and other research platform offerings.\n\n - Build high‑quality examples, reference implementations, and “recipes” that make it easy for others to extend the stack.\n\n - Prototype agents and eval harnesses tailored to real-world use cases and external systems.\n\n - Pair with technical end‑users (research teams, infra‑heavy customers, open‑source contributors) to design environments, evals, and verifiers that reflect real workloads.\n\n\n\nPost-training & Reinforcement Learning\n\n - Design and implement novel RL and post-training methods (RLHF, RLVR, GRPO, etc.) to align large models with domain-specific tasks.\n\n - Build evaluations and harnesses and to measure reasoning, robustness, and agentic behavior in real-world workflows.\n\n - Prototype multi-agent and memory-augmented systems to expand capabilities for downstream applications.\n\n - Experiment with post-training recipes to optimize downstream performance.  \n\n\n\nAgent Development & Infrastructure\n\n - Rapidly prototype and iterate on AI agents for automation, workflow orchestration, and decision-making.\n\n - Extend and integrate with agent frameworks to support evolving feature requests and performance requirements.\n\n - Architect and maintain distributed training/inference pipelines, ensuring scalability and cost efficiency.\n\n - Develop observability and monitoring (Prometheus, Grafana, tracing) to ensure reliability and performance in production deployments.\n\n\n\n\nREQUIREMENTS\n\n - Strong background in machine learning engineering, with experience in post-training, RL, or large-scale model alignment. \n\n - Experience with agent frameworks and tooling (e.g. DSPy, LangGraph, MCP, Stagehand).\n\n - Familiarity with distributed training/inference frameworks (e.g., vLLM, sglang, Accelerate, Ray, Torch).\n\n - Track record of research contributions (publications, open-source contributions, benchmarks) in ML/RL.\n\n - Passion for advancing the state-of-the-art in reasoning and building practical, agentic AI systems.\n\n - Strong technical writing abilities (documentation, blogs, papers) and research taste.\n\n - Eagerness to drive collaborations with external partners and engage with the broader open-source community.\n\n\n\n\nNICE-TO-HAVES\n\n - Experience with web programming (React, TypeScript, Next.js).\n\n - Experience running LLM evaluations and/or synthetic data generation.\n\n - Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).\n   \n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $150-300k + equity incentives\n\n - Flexible Work (San Francisco or hybrid-remote)\n\n - Visa Sponsorship & relocation support\n\n - Professional Development budget\n\n - Team Off-sites & conference attendance\n\n\n\nGROWTH OPPORTUNITY\n\nYou’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:\n\n - Shape the evolution of agent-driven solutions—from research breakthroughs to production systems used by real customers.\n\n - Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL and post-training.\n\n - Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.\n\nIf you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.\n\n\n\nReady to build the open superintelligence infrastructure of tomorrow?\nApply now to help us make powerful, open AGI accessible to everyone."},{"id":"4c6ccfd6-6512-4905-979a-6dcc6d64a935","title":"Head of Growth","department":"Growth","team":"Growth","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:41:56.858+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/4c6ccfd6-6512-4905-979a-6dcc6d64a935","applyUrl":"https://jobs.ashbyhq.com/primeintellect/4c6ccfd6-6512-4905-979a-6dcc6d64a935/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><strong>Your Role</strong></h2><p style=\"min-height:1.5em\">As <strong>Head of Growth</strong>, you’ll lead everything that connects our technology to the market — spanning sales, marketing, partnerships, and customer success. You’ll define how Prime Intellect tells its story, close large-scale post-training and compute contracts, and build the systems that let us scale revenue efficiently. This is a high-leverage role combining strategy, execution, and team building — perfect for a hybrid commercial operator who thrives at the intersection of infrastructure and intelligence.</p><p style=\"min-height:1.5em\"></p><h2><strong>Responsibilities</strong></h2><p style=\"min-height:1.5em\"><strong>Strategy &amp; Vision</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and lead a cross-functional Growth organization spanning Sales, Marketing, Partnerships, and Customer Success.</p></li><li><p style=\"min-height:1.5em\">Define our go-to-market strategy for RL infrastructure pricing, packaging, and positioning.</p></li><li><p style=\"min-height:1.5em\">Own revenue forecasting, pipeline visibility, and operational cadence (CRM, dashboards, and forecasting systems).</p></li><li><p style=\"min-height:1.5em\">Design data-driven systems for deal tracking, reporting, and forecasting accuracy.</p></li></ul><p style=\"min-height:1.5em\"><strong>Sales &amp; Partnerships</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Lead enterprise sales cycles for post-training and multi-node cluster deals (64+ GPUs, 6+ month durations).</p></li><li><p style=\"min-height:1.5em\">Develop repeatable playbooks for design-partner conversions and enterprise onboarding.</p></li><li><p style=\"min-height:1.5em\">Build strategic partnerships with compute providers, AI companies, and research labs to expand our ecosystem.</p></li><li><p style=\"min-height:1.5em\">Identify and nurture high-value leads through targeted outbound and inbound growth strategies.</p></li></ul><p style=\"min-height:1.5em\"><strong>Marketing</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Drive developer and enterprise awareness through campaigns, launches, community, and content.</p></li><li><p style=\"min-height:1.5em\">Translate technical features into clear market narratives and differentiated positioning.</p></li><li><p style=\"min-height:1.5em\">Partner with Product to align market feedback with roadmap and developer onboarding.</p></li><li><p style=\"min-height:1.5em\">Run quantitative experiments on activation, conversion, and usage metrics.</p></li></ul><p style=\"min-height:1.5em\"><strong>Customer Success / Account Management</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build the CS motion across onboarding, usage analytics, renewals, and expansion workflows.</p></li><li><p style=\"min-height:1.5em\">Implement CRM-based renewal tracking and feedback loops into product and operations.</p></li><li><p style=\"min-height:1.5em\">Establish systems for continuous measurement of customer value and satisfaction.</p></li></ul><p style=\"min-height:1.5em\"><strong>Growth Operations</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design scalable processes for deal management, supplier bidding, contract ops, and revenue tracking.</p></li><li><p style=\"min-height:1.5em\">Partner with Operations and Finance on budgeting, hiring, and legal structures that support rapid scale.</p></li><li><p style=\"min-height:1.5em\">Implement sales technology stack and CRM architecture to enable data-driven decision making.</p></li></ul><h3><strong>What We’re Looking For</strong></h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">5+ years leading growth, GTM, or revenue functions at a B2B or infrastructure startup.</p></li><li><p style=\"min-height:1.5em\">Fluent in both technical and commercial conversations — comfortable discussing GPUs, APIs, and pricing models.</p></li><li><p style=\"min-height:1.5em\">Proven ability to build scalable systems (CRM, forecasting, dashboards) and clean operational processes.</p></li><li><p style=\"min-height:1.5em\">Track record of closing enterprise-scale infrastructure or developer-tooling deals.</p></li><li><p style=\"min-height:1.5em\">Analytical, curious, and comfortable in high-ambiguity, fast-moving environments.</p></li><li><p style=\"min-height:1.5em\">Strong communication and leadership skills with experience building small, high-performing teams.</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience pricing or selling infrastructure or developer tools.</p></li><li><p style=\"min-height:1.5em\">Familiarity with enterprise AI, cloud infrastructure, or post-training markets.</p></li><li><p style=\"min-height:1.5em\">Early-stage operator mindset — bias for building playbooks, not inheriting them.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150-300k<strong> </strong>+ equity incentives</p></li><li><p style=\"min-height:1.5em\"><strong>Flexible Work</strong> (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\"><strong>Visa Sponsorship</strong> &amp; relocation support</p></li><li><p style=\"min-height:1.5em\"><strong>Professional Development</strong> budget</p></li><li><p style=\"min-height:1.5em\"><strong>Team Off-sites</strong> &amp; conference attendance</p></li><li><p style=\"min-height:1.5em\"><strong>Opportunity to Shape Decentralized AI</strong> at Prime Intellect</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nAs Head of Growth, you’ll lead everything that connects our technology to the market — spanning sales, marketing, partnerships, and customer success. You’ll define how Prime Intellect tells its story, close large-scale post-training and compute contracts, and build the systems that let us scale revenue efficiently. This is a high-leverage role combining strategy, execution, and team building — perfect for a hybrid commercial operator who thrives at the intersection of infrastructure and intelligence.\n\n\n\n\nRESPONSIBILITIES\n\nStrategy & Vision\n\n - Build and lead a cross-functional Growth organization spanning Sales, Marketing, Partnerships, and Customer Success.\n\n - Define our go-to-market strategy for RL infrastructure pricing, packaging, and positioning.\n\n - Own revenue forecasting, pipeline visibility, and operational cadence (CRM, dashboards, and forecasting systems).\n\n - Design data-driven systems for deal tracking, reporting, and forecasting accuracy.\n\nSales & Partnerships\n\n - Lead enterprise sales cycles for post-training and multi-node cluster deals (64+ GPUs, 6+ month durations).\n\n - Develop repeatable playbooks for design-partner conversions and enterprise onboarding.\n\n - Build strategic partnerships with compute providers, AI companies, and research labs to expand our ecosystem.\n\n - Identify and nurture high-value leads through targeted outbound and inbound growth strategies.\n\nMarketing\n\n - Drive developer and enterprise awareness through campaigns, launches, community, and content.\n\n - Translate technical features into clear market narratives and differentiated positioning.\n\n - Partner with Product to align market feedback with roadmap and developer onboarding.\n\n - Run quantitative experiments on activation, conversion, and usage metrics.\n\nCustomer Success / Account Management\n\n - Build the CS motion across onboarding, usage analytics, renewals, and expansion workflows.\n\n - Implement CRM-based renewal tracking and feedback loops into product and operations.\n\n - Establish systems for continuous measurement of customer value and satisfaction.\n\nGrowth Operations\n\n - Design scalable processes for deal management, supplier bidding, contract ops, and revenue tracking.\n\n - Partner with Operations and Finance on budgeting, hiring, and legal structures that support rapid scale.\n\n - Implement sales technology stack and CRM architecture to enable data-driven decision making.\n\n\nWHAT WE’RE LOOKING FOR\n\n - 5+ years leading growth, GTM, or revenue functions at a B2B or infrastructure startup.\n\n - Fluent in both technical and commercial conversations — comfortable discussing GPUs, APIs, and pricing models.\n\n - Proven ability to build scalable systems (CRM, forecasting, dashboards) and clean operational processes.\n\n - Track record of closing enterprise-scale infrastructure or developer-tooling deals.\n\n - Analytical, curious, and comfortable in high-ambiguity, fast-moving environments.\n\n - Strong communication and leadership skills with experience building small, high-performing teams.\n\nBonus:\n\n - Experience pricing or selling infrastructure or developer tools.\n\n - Familiarity with enterprise AI, cloud infrastructure, or post-training markets.\n\n - Early-stage operator mindset — bias for building playbooks, not inheriting them.\n\n\n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $150-300k + equity incentives\n\n - Flexible Work (remote or San Francisco)\n\n - Visa Sponsorship & relocation support\n\n - Professional Development budget\n\n - Team Off-sites & conference attendance\n\n - Opportunity to Shape Decentralized AI at Prime Intellect"},{"id":"8706578d-5a01-4270-9d43-ed9cd998a982","title":"Member of Technical Staff - Training Platform","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:45:47.645+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/8706578d-5a01-4270-9d43-ed9cd998a982","applyUrl":"https://jobs.ashbyhq.com/primeintellect/8706578d-5a01-4270-9d43-ed9cd998a982/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll help build our hosted <strong>training platform -</strong> the product that lets users launch LoRA and full fine-tuning runs on managed GPU clusters with a single API call or a few clicks. The role spans the developer-facing platform and the underlying Kubernetes-based training infrastructure that runs the jobs. </p><p style=\"min-height:1.5em\"></p><h2>Core Technical Responsibilities </h2><p style=\"min-height:1.5em\"></p><h3>Hosted Training Infrastructure </h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and operate Kubernetes-based training and inference orchestration across multi-cluster, multi-cloud GPU fleets</p></li><li><p style=\"min-height:1.5em\">Build and maintain Helm charts that compose trainers, inference servers, environment servers, and supporting services into reproducible \"Training stacks\"</p></li><li><p style=\"min-height:1.5em\">Develop the Python control-plane agents that watch pods, report run state to the platform, and keep clusters in sync</p></li><li><p style=\"min-height:1.5em\">Implement scheduling and autoscaling for heterogeneous hardware (H100/H200/B200) using KEDA, LeaderWorkerSet, taints/tolerations, and gang scheduling</p></li><li><p style=\"min-height:1.5em\">Run a tight GitOps workflow - every change ships through PRs, Helm values, and CI</p></li><li><p style=\"min-height:1.5em\">Build node-local model caches, checkpoint pipelines, and shared storage for fast cold starts</p></li><li><p style=\"min-height:1.5em\">Operate the observability stack (Prometheus, Grafana, Loki, DCGM) and make GPU cluster debugging fast</p></li></ul><h3>Platform Development</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build the developer-facing surfaces for hosted training: job submission, live run monitoring, logs, metrics, model/adapter management, comparisons</p></li><li><p style=\"min-height:1.5em\">Develop FastAPI backend services and REST APIs that bridge the platform to running clusters</p></li><li><p style=\"min-height:1.5em\">Build real-time monitoring and debugging tools (streaming logs, step-level metrics, failure analysis)</p></li><li><p style=\"min-height:1.5em\">Ship product UI in Next.js / React / TypeScript with shadcn, Tailwind, tRPC, and TanStack Query</p></li></ul><h3>Research Bridge</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Interface with the RL trainer, inference servers, and environment servers running inside our clusters</p></li><li><p style=\"min-height:1.5em\">Productize new training capabilities (new model architectures, RL algorithms, modes)</p></li></ul><h2></h2><h2>Technical Requirements</h2><p style=\"min-height:1.5em\">We're looking for engineers who are fluent across three areas - you don't need to be the world's best at any one, but you should have real depth in all three and a clear point of view on how they connect.</p><p style=\"min-height:1.5em\"></p><h3>AI &amp; GPU Landscape</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong working knowledge of the modern AI stack - open model families, finetuning techniques (LoRA, QLoRA, full FT, RLHF/RLAIF), inference engines (vLLM, SGLang, TensorRT-LLM)</p></li><li><p style=\"min-height:1.5em\">Familiarity with GPU hardware tradeoffs (H100 / H200 / B200, NVLink, interconnects, memory hierarchy) and what they mean for training and inference workloads</p></li><li><p style=\"min-height:1.5em\">Understanding of distributed training fundamentals (data/tensor/pipeline/expert parallelism, NCCL, multi-node scheduling)</p></li><li><p style=\"min-height:1.5em\">Awareness of what's happening at the frontier - new models, training methods, infra patterns - and the ability to translate that into product decisions</p><p style=\"min-height:1.5em\"></p></li></ul><h3>Kubernetes &amp; Infrastructure</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong Kubernetes operations experience - Helm, CRDs, operators, KEDA, gang scheduling, GPU operator</p></li><li><p style=\"min-height:1.5em\">Comfortable debugging real production clusters (kubectl, pod lifecycle, node issues, networking)</p></li><li><p style=\"min-height:1.5em\">Cloud platform experience (GCP preferred - GCS, GKE, Cloud Run, Cloud Tasks)</p></li><li><p style=\"min-height:1.5em\">Infrastructure automation (Helm, Terraform, Ansible) and a GitOps mindset</p></li><li><p style=\"min-height:1.5em\">Observability: Prometheus, Grafana, Loki, OpenTelemetry, DCGM</p></li><li><p style=\"min-height:1.5em\">Linux fundamentals: networking, namespaces, performance tuning</p><p style=\"min-height:1.5em\"></p></li></ul><h3>Programming &amp; Platform</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong Python backend development (FastAPI, async, SQLAlchemy)</p></li><li><p style=\"min-height:1.5em\">Comfortable building Python control-plane agents that talk to Kubernetes APIs</p></li><li><p style=\"min-height:1.5em\">Modern frontend development (TypeScript, React/Next.js, Tailwind, shadcn) - enough to ship product surfaces end-to-end</p></li><li><p style=\"min-height:1.5em\">REST and tRPC API design</p></li><li><p style=\"min-height:1.5em\">Experience building developer tools, dashboards, and live-monitoring UIs</p><p style=\"min-height:1.5em\"></p></li></ul><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation $150K–$300K with significant equity</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangement (remote or San Francisco office)</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">Opportunity to shape the future of decentralized AI development</p><p style=\"min-height:1.5em\"></p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source work.</p><p style=\"min-height:1.5em\">We value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Ready to help shape the future of AI?</strong> Apply now and join us in our mission to make powerful AI models accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nROLE IMPACT\n\nYou'll help build our hosted training platform - the product that lets users launch LoRA and full fine-tuning runs on managed GPU clusters with a single API call or a few clicks. The role spans the developer-facing platform and the underlying Kubernetes-based training infrastructure that runs the jobs. \n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES \n\n\n\n\nHOSTED TRAINING INFRASTRUCTURE \n\n - Design and operate Kubernetes-based training and inference orchestration across multi-cluster, multi-cloud GPU fleets\n\n - Build and maintain Helm charts that compose trainers, inference servers, environment servers, and supporting services into reproducible \"Training stacks\"\n\n - Develop the Python control-plane agents that watch pods, report run state to the platform, and keep clusters in sync\n\n - Implement scheduling and autoscaling for heterogeneous hardware (H100/H200/B200) using KEDA, LeaderWorkerSet, taints/tolerations, and gang scheduling\n\n - Run a tight GitOps workflow - every change ships through PRs, Helm values, and CI\n\n - Build node-local model caches, checkpoint pipelines, and shared storage for fast cold starts\n\n - Operate the observability stack (Prometheus, Grafana, Loki, DCGM) and make GPU cluster debugging fast\n\n\nPLATFORM DEVELOPMENT\n\n - Build the developer-facing surfaces for hosted training: job submission, live run monitoring, logs, metrics, model/adapter management, comparisons\n\n - Develop FastAPI backend services and REST APIs that bridge the platform to running clusters\n\n - Build real-time monitoring and debugging tools (streaming logs, step-level metrics, failure analysis)\n\n - Ship product UI in Next.js / React / TypeScript with shadcn, Tailwind, tRPC, and TanStack Query\n\n\nRESEARCH BRIDGE\n\n - Interface with the RL trainer, inference servers, and environment servers running inside our clusters\n\n - Productize new training capabilities (new model architectures, RL algorithms, modes)\n\n\n\n\n\nTECHNICAL REQUIREMENTS\n\nWe're looking for engineers who are fluent across three areas - you don't need to be the world's best at any one, but you should have real depth in all three and a clear point of view on how they connect.\n\n\n\n\nAI & GPU LANDSCAPE\n\n - Strong working knowledge of the modern AI stack - open model families, finetuning techniques (LoRA, QLoRA, full FT, RLHF/RLAIF), inference engines (vLLM, SGLang, TensorRT-LLM)\n\n - Familiarity with GPU hardware tradeoffs (H100 / H200 / B200, NVLink, interconnects, memory hierarchy) and what they mean for training and inference workloads\n\n - Understanding of distributed training fundamentals (data/tensor/pipeline/expert parallelism, NCCL, multi-node scheduling)\n\n - Awareness of what's happening at the frontier - new models, training methods, infra patterns - and the ability to translate that into product decisions\n   \n   \n\n\nKUBERNETES & INFRASTRUCTURE\n\n - Strong Kubernetes operations experience - Helm, CRDs, operators, KEDA, gang scheduling, GPU operator\n\n - Comfortable debugging real production clusters (kubectl, pod lifecycle, node issues, networking)\n\n - Cloud platform experience (GCP preferred - GCS, GKE, Cloud Run, Cloud Tasks)\n\n - Infrastructure automation (Helm, Terraform, Ansible) and a GitOps mindset\n\n - Observability: Prometheus, Grafana, Loki, OpenTelemetry, DCGM\n\n - Linux fundamentals: networking, namespaces, performance tuning\n   \n   \n\n\nPROGRAMMING & PLATFORM\n\n - Strong Python backend development (FastAPI, async, SQLAlchemy)\n\n - Comfortable building Python control-plane agents that talk to Kubernetes APIs\n\n - Modern frontend development (TypeScript, React/Next.js, Tailwind, shadcn) - enough to ship product surfaces end-to-end\n\n - REST and tRPC API design\n\n - Experience building developer tools, dashboards, and live-monitoring UIs\n   \n   \n\n\nWHAT WE OFFER\n\n - Cash compensation $150K–$300K with significant equity\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n - Opportunity to shape the future of decentralized AI development\n   \n   \n\n\nGROWTH OPPORTUNITY\n\nYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source work.\n\nWe value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you.\n\n\n\nReady to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone."},{"id":"82084989-3721-475b-8253-46faab74a0ab","title":"Compute Finance and Strategy","department":"Compute / Finance","team":"Compute / Finance","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:35:11.447+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/82084989-3721-475b-8253-46faab74a0ab","applyUrl":"https://jobs.ashbyhq.com/primeintellect/82084989-3721-475b-8253-46faab74a0ab/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h1><strong>Your Role</strong></h1><p style=\"min-height:1.5em\">Compute is the foundational input of the AI era. The companies, models, and capabilities that define the next decade will be shaped by who has access to compute, on what terms, at what economics, and how it gets allocated across the systems that get built on top of it. The financial and operational architecture for an asset class of this consequence is still being built, and the playbooks for navigating it don't yet exist. The people who write them will define how the AI infrastructure industry develops over the next decade.</p><p style=\"min-height:1.5em\">You will own the analytical foundation for how we understand global compute markets: pricing supply across regions and term lengths, modeling the economics of large GPU commitments, evaluating neoclouds and hyperscalers, and turning that work into provider decisions, commercial structures, and customer-facing products.</p><p style=\"min-height:1.5em\">The work sits at the intersection of infrastructure, finance, and AI systems. You will evaluate questions like when an H200 cluster is the right fit versus GB200 or GB300, how networking and storage constraints affect real workload performance, how utilization assumptions change the economics of a multi-year commitment, and how regional power, colo, and capital costs flow through to GPU-hour pricing. You will diligence providers not just on headline price, but on delivery timeline, cluster architecture, reliability, support model, contractual risk, and ability to serve frontier AI workloads.</p><p style=\"min-height:1.5em\">The decisions you support will directly shape Prime Intellect’s ability to deliver high-quality compute to researchers, AI labs, and enterprises building on top of our stack.</p><p style=\"min-height:1.5em\"></p><h1><strong>Responsibilities</strong></h1><p style=\"min-height:1.5em\"><strong>Compute Economics</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and own the financial models that price our compute supply: per-cluster economics, contract structures, hardware generation comparisons, geographic and provider differentials</p></li><li><p style=\"min-height:1.5em\">Model the economics of every meaningful supply decision — reserved vs. spot tradeoffs, term length, commitment level, hardware generation, provider mix, geography</p></li><li><p style=\"min-height:1.5em\">Own margin architecture: margin by workload, customer, product, and contract, so we always know what's actually profitable and where the leverage is</p></li><li><p style=\"min-height:1.5em\">Model the long-term P&amp;L consequences of today's supply bets under multiple demand and pricing scenarios</p></li></ul><p style=\"min-height:1.5em\"><strong>Strategic Bets &amp; Capital Allocation</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Partner with leadership on the biggest decisions the company makes: which providers to commit to, which hardware generations, what geographies to lean into, how aggressively to scale</p></li><li><p style=\"min-height:1.5em\">Build the financial frameworks that turn ambiguous strategic questions into decisions we can make with conviction</p></li><li><p style=\"min-height:1.5em\">Own the long-range plan, scenario models, and capital allocation framework across compute, headcount, and product investment</p></li></ul><p style=\"min-height:1.5em\"><strong>Provider Engagement &amp; Diligence</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Engage directly with neoclouds, hyperscalers, and emerging providers on economic and technical diligence</p></li><li><p style=\"min-height:1.5em\">Run the financial side of supply qualification — what we accept, what we reject, what we negotiate harder on</p></li><li><p style=\"min-height:1.5em\">Translate technical performance characteristics into commercial recommendations</p></li><li><p style=\"min-height:1.5em\">Build the repeatable analytical process for evaluating new entrants to the global supply market</p></li></ul><p style=\"min-height:1.5em\"><strong>Market Intelligence</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Track pricing, availability, and provider dynamics continuously across every major market</p></li><li><p style=\"min-height:1.5em\">Build Prime Intellect's view of the global compute market — who's credible, who's mispriced, where supply is tightening, where the next wave of capacity is coming online</p></li><li><p style=\"min-height:1.5em\">Develop the analytical basis for our market positioning: when to commit hard, when to hold flexibility, where to lean in geographically</p></li></ul><p style=\"min-height:1.5em\"><strong>Cross-functional Partnership</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Partner with Strategic Finance on how compute economics flow through to the company P&amp;L</p></li><li><p style=\"min-height:1.5em\">Partner with Engineering on the technical performance characteristics that drive cluster economics</p></li><li><p style=\"min-height:1.5em\">Partner with Sales and Product on pricing strategy for consumption-based and hybrid products</p></li><li><p style=\"min-height:1.5em\">Build board-ready analyses on supply strategy, capital allocation, and market positioning</p></li></ul><p style=\"min-height:1.5em\"><strong>What We're Looking For</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">4–7+ years in roles that combine financial rigor with real-world strategic or operational engagement. Backgrounds we'd find compelling include:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Investment banking, private equity, or growth equity with exposure to infrastructure, cloud, semiconductors, or technology</p></li><li><p style=\"min-height:1.5em\">Quantitative or strategist roles at hedge funds, commodities desks, or trading firms</p></li><li><p style=\"min-height:1.5em\">Infrastructure investing, project finance, or structured credit</p></li><li><p style=\"min-height:1.5em\">Strategic finance or BizOps at a high-growth cloud, AI infrastructure, or compute-intensive company</p></li></ul></li><li><p style=\"min-height:1.5em\">Exceptional modeling and analytical skills — you build the models yourself, and your models reflect how the business actually works</p></li><li><p style=\"min-height:1.5em\">Genuine technical curiosity. You don't need deep technical background to start, but you should be excited to develop fluency in GPU architectures, networking, cluster performance, and what makes one piece of compute economically different from another</p></li><li><p style=\"min-height:1.5em\">Strong commercial and strategic judgment — you understand that finance's job is to drive better decisions, not produce more analysis</p></li><li><p style=\"min-height:1.5em\">Comfortable engaging directly with vendors, partners, and senior counterparts at provider companies</p></li><li><p style=\"min-height:1.5em\">Ability to operate across registers — building rigorous models, briefing leadership on strategic implications, and running diligence with senior counterparts at provider companies</p></li><li><p style=\"min-height:1.5em\">High ownership — you see gaps and build the fix before anyone asks</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Direct experience modeling datacenter, colocation, cloud, or power/energy economics</p></li><li><p style=\"min-height:1.5em\">Background covering AI infrastructure, cloud providers, semiconductors, or compute marketplaces from the banking, investing, or trading side</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with cluster benchmarking, training/inference workload economics, or compute marketplaces</p></li></ul><p style=\"min-height:1.5em\"></p><h1><strong>Why This Role</strong></h1><p style=\"min-height:1.5em\">Compute economics is becoming one of the most consequential domains in technology, and almost no one is approaching it with the rigor it deserves. You'll be in the room for the decisions shaping Prime Intellect's future and, in real ways, the future of open AI infrastructure. You'll work directly with leadership on the calls that define the company, develop deep expertise in a market most finance professionals only read about, and build a foundation in compute economics that is increasingly valuable across the industry.</p><p style=\"min-height:1.5em\"></p><h1><strong>What We Offer</strong></h1><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $200-300k + meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nCompute is the foundational input of the AI era. The companies, models, and capabilities that define the next decade will be shaped by who has access to compute, on what terms, at what economics, and how it gets allocated across the systems that get built on top of it. The financial and operational architecture for an asset class of this consequence is still being built, and the playbooks for navigating it don't yet exist. The people who write them will define how the AI infrastructure industry develops over the next decade.\n\nYou will own the analytical foundation for how we understand global compute markets: pricing supply across regions and term lengths, modeling the economics of large GPU commitments, evaluating neoclouds and hyperscalers, and turning that work into provider decisions, commercial structures, and customer-facing products.\n\nThe work sits at the intersection of infrastructure, finance, and AI systems. You will evaluate questions like when an H200 cluster is the right fit versus GB200 or GB300, how networking and storage constraints affect real workload performance, how utilization assumptions change the economics of a multi-year commitment, and how regional power, colo, and capital costs flow through to GPU-hour pricing. You will diligence providers not just on headline price, but on delivery timeline, cluster architecture, reliability, support model, contractual risk, and ability to serve frontier AI workloads.\n\nThe decisions you support will directly shape Prime Intellect’s ability to deliver high-quality compute to researchers, AI labs, and enterprises building on top of our stack.\n\n\n\n\nRESPONSIBILITIES\n\nCompute Economics\n\n - Build and own the financial models that price our compute supply: per-cluster economics, contract structures, hardware generation comparisons, geographic and provider differentials\n\n - Model the economics of every meaningful supply decision — reserved vs. spot tradeoffs, term length, commitment level, hardware generation, provider mix, geography\n\n - Own margin architecture: margin by workload, customer, product, and contract, so we always know what's actually profitable and where the leverage is\n\n - Model the long-term P&L consequences of today's supply bets under multiple demand and pricing scenarios\n\nStrategic Bets & Capital Allocation\n\n - Partner with leadership on the biggest decisions the company makes: which providers to commit to, which hardware generations, what geographies to lean into, how aggressively to scale\n\n - Build the financial frameworks that turn ambiguous strategic questions into decisions we can make with conviction\n\n - Own the long-range plan, scenario models, and capital allocation framework across compute, headcount, and product investment\n\nProvider Engagement & Diligence\n\n - Engage directly with neoclouds, hyperscalers, and emerging providers on economic and technical diligence\n\n - Run the financial side of supply qualification — what we accept, what we reject, what we negotiate harder on\n\n - Translate technical performance characteristics into commercial recommendations\n\n - Build the repeatable analytical process for evaluating new entrants to the global supply market\n\nMarket Intelligence\n\n - Track pricing, availability, and provider dynamics continuously across every major market\n\n - Build Prime Intellect's view of the global compute market — who's credible, who's mispriced, where supply is tightening, where the next wave of capacity is coming online\n\n - Develop the analytical basis for our market positioning: when to commit hard, when to hold flexibility, where to lean in geographically\n\nCross-functional Partnership\n\n - Partner with Strategic Finance on how compute economics flow through to the company P&L\n\n - Partner with Engineering on the technical performance characteristics that drive cluster economics\n\n - Partner with Sales and Product on pricing strategy for consumption-based and hybrid products\n\n - Build board-ready analyses on supply strategy, capital allocation, and market positioning\n\nWhat We're Looking For\n\n - 4–7+ years in roles that combine financial rigor with real-world strategic or operational engagement. Backgrounds we'd find compelling include:\n   \n   - Investment banking, private equity, or growth equity with exposure to infrastructure, cloud, semiconductors, or technology\n   \n   - Quantitative or strategist roles at hedge funds, commodities desks, or trading firms\n   \n   - Infrastructure investing, project finance, or structured credit\n   \n   - Strategic finance or BizOps at a high-growth cloud, AI infrastructure, or compute-intensive company\n\n - Exceptional modeling and analytical skills — you build the models yourself, and your models reflect how the business actually works\n\n - Genuine technical curiosity. You don't need deep technical background to start, but you should be excited to develop fluency in GPU architectures, networking, cluster performance, and what makes one piece of compute economically different from another\n\n - Strong commercial and strategic judgment — you understand that finance's job is to drive better decisions, not produce more analysis\n\n - Comfortable engaging directly with vendors, partners, and senior counterparts at provider companies\n\n - Ability to operate across registers — building rigorous models, briefing leadership on strategic implications, and running diligence with senior counterparts at provider companies\n\n - High ownership — you see gaps and build the fix before anyone asks\n\n - AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster\n\nBonus:\n\n - Direct experience modeling datacenter, colocation, cloud, or power/energy economics\n\n - Background covering AI infrastructure, cloud providers, semiconductors, or compute marketplaces from the banking, investing, or trading side\n\n - Hands-on experience with cluster benchmarking, training/inference workload economics, or compute marketplaces\n\n\n\n\nWHY THIS ROLE\n\nCompute economics is becoming one of the most consequential domains in technology, and almost no one is approaching it with the rigor it deserves. You'll be in the room for the decisions shaping Prime Intellect's future and, in real ways, the future of open AI infrastructure. You'll work directly with leadership on the calls that define the company, develop deep expertise in a market most finance professionals only read about, and build a foundation in compute economics that is increasingly valuable across the industry.\n\n\n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $200-300k + meaningful equity\n\n - Flexible work (remote or San Francisco)\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"73f42d73-f967-4082-b599-b8914135a6b3","title":"Applied Research - Forward-Deployed","department":"Applied Research","team":"Applied Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:34:29.004+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/73f42d73-f967-4082-b599-b8914135a6b3","applyUrl":"https://jobs.ashbyhq.com/primeintellect/73f42d73-f967-4082-b599-b8914135a6b3/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2><strong><br /></strong>About the Role</h2><p style=\"min-height:1.5em\">We're looking for a Forward-Deployed Research Engineer (FDRE) to serve as the primary technical interface between Prime Intellect and our most important customers: AI companies, research labs, and enterprises running post-training and agentic RL on our platform.</p><p style=\"min-height:1.5em\">This is not a traditional research role. You'll spend most of your time embedded with customers, understanding their models, workflows, and goals. Then, you'll translate those objectives into concrete training runs, environment designs, evaluation harnesses, and deployment recipes using the Lab stack. You are the person who makes the platform work in practice for real workloads.</p><p style=\"min-height:1.5em\">You'll work closely with our research, product, and infrastructure teams to feed field insights back into the platform, shaping what we build next based on what customers actually need.</p><h3></h3><h2>What You'll Do</h2><h3>Customer Engagement &amp; Technical Delivery</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Embed directly with strategic customers to understand their agent architectures, failure modes, and product goals</p></li><li><p style=\"min-height:1.5em\">Design and build custom RL environments, evaluation harnesses, and verifiers that capture what \"good\" looks like for each customer's domain</p></li><li><p style=\"min-height:1.5em\">Architect agent scaffolding — tool use, multi-step reasoning, memory, sandbox execution — tailored to customer workflows</p></li><li><p style=\"min-height:1.5em\">Configure and launch training runs on Lab, iterating on reward functions, rollout strategies, and evaluation criteria</p></li><li><p style=\"min-height:1.5em\">Serve as the technical lead for engagements end-to-end: from discovery through deployed, improved models</p></li></ul><h3>Platform Feedback &amp; Ecosystem</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Identify repeatable patterns from customer engagements and codify them into reference implementations, templates, and documentation</p></li><li><p style=\"min-height:1.5em\">Serve as the voice of the customer internally, shaping the roadmap for Lab, verifiers, the Environments Hub, and training infrastructure</p></li><li><p style=\"min-height:1.5em\">Build high-quality examples and \"recipes\" that make it easy for new customers and open-source contributors to extend the stack</p></li><li><p style=\"min-height:1.5em\">Contribute to technical content (blog posts, tutorials, case studies) that demonstrates real-world platform usage</p></li></ul><h3>Applied Research &amp; Experimentation</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Develop novel evaluation methodologies for agentic behavior — multi-step reasoning, tool use correctness, recovery from failure, long-horizon task completion</p></li><li><p style=\"min-height:1.5em\">Prototype and iterate on agent harnesses for real-world tasks: code generation, workflow automation, document processing, and more</p></li><li><p style=\"min-height:1.5em\">Experiment with reward design, rubric construction, and environment shaping to improve training signal quality</p></li><li><p style=\"min-height:1.5em\">Stay current on the frontier of agentic AI, evals, and post-training methods, and bring that knowledge directly into customer work</p></li></ul><h2>What We're Looking For</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Deep hands-on experience building, evaluating, or deploying LLM-based agents in the past 1–2 years — you've seen what breaks in production and know what good evals look like</p></li><li><p style=\"min-height:1.5em\">Strong intuition for evaluation design: you can look at a customer's agent and quickly identify what to measure, how to construct a rubric, and where the reward signal is weak</p></li><li><p style=\"min-height:1.5em\">Working understanding of RL and post-training concepts (GRPO, RLHF, reward modeling, SFT) — you don't need to have written a trainer from scratch, but you should understand what the knobs do and why they matter</p></li><li><p style=\"min-height:1.5em\">Strong Python skills and comfort with the modern AI stack (Hugging Face, inference engines, agent frameworks)</p></li><li><p style=\"min-height:1.5em\">Experience in a customer-facing or consulting-adjacent technical role, or as a technical founder — you're comfortable in a room with a customer's engineering team figuring out what to build</p></li><li><p style=\"min-height:1.5em\">Excellent written and verbal communication — you can write a clear environment spec, a compelling case study, and a useful Slack message to a frustrated customer</p></li><li><p style=\"min-height:1.5em\">High agency and comfort with ambiguity. You don't wait for specs; you scope the problem, ship a solution, and iterate</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Nice-to-Haves</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with agent frameworks and tooling (DSPy, LangGraph, MCP, Stagehand, browser automation)</p></li><li><p style=\"min-height:1.5em\">Experience building or running LLM evaluation pipelines at scale (benchmarks, synthetic data generation, model grading)</p></li><li><p style=\"min-height:1.5em\">Research experience — publications, open-source contributions, or benchmarks in ML/RL/agents</p></li><li><p style=\"min-height:1.5em\">Familiarity with sandbox/code execution environments for agent evaluation</p></li><li><p style=\"min-height:1.5em\">Web programming experience (React, TypeScript, Next.js) for building demos and customer-facing tooling<br /></p></li></ul><h2><strong>What We Offer</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Cash Compensation Range of $150-300k </strong>+ equity incentives</p></li><li><p style=\"min-height:1.5em\"><strong>Flexible Work</strong> (San Francisco or hybrid-remote)</p></li><li><p style=\"min-height:1.5em\"><strong>Visa Sponsorship</strong> &amp; relocation support</p></li><li><p style=\"min-height:1.5em\"><strong>Professional Development</strong> budget</p></li><li><p style=\"min-height:1.5em\"><strong>Team Off-sites</strong> &amp; conference attendance</p></li></ul><h2><strong><br />Growth Opportunity</strong></h2><p style=\"min-height:1.5em\">You’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Shape the evolution of agent-driven solutions—from research breakthroughs to production systems used by real customers.</p></li><li><p style=\"min-height:1.5em\">Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL and post-training.</p></li><li><p style=\"min-height:1.5em\">Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.</p></li></ul><p style=\"min-height:1.5em\">If you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Ready to build the open superintelligence infrastructure of tomorrow?</strong><br />Apply now to help us make powerful, open AGI accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nABOUT THE ROLE\n\nWe're looking for a Forward-Deployed Research Engineer (FDRE) to serve as the primary technical interface between Prime Intellect and our most important customers: AI companies, research labs, and enterprises running post-training and agentic RL on our platform.\n\nThis is not a traditional research role. You'll spend most of your time embedded with customers, understanding their models, workflows, and goals. Then, you'll translate those objectives into concrete training runs, environment designs, evaluation harnesses, and deployment recipes using the Lab stack. You are the person who makes the platform work in practice for real workloads.\n\nYou'll work closely with our research, product, and infrastructure teams to feed field insights back into the platform, shaping what we build next based on what customers actually need.\n\n\n\n\n\nWHAT YOU'LL DO\n\n\nCUSTOMER ENGAGEMENT & TECHNICAL DELIVERY\n\n - Embed directly with strategic customers to understand their agent architectures, failure modes, and product goals\n\n - Design and build custom RL environments, evaluation harnesses, and verifiers that capture what \"good\" looks like for each customer's domain\n\n - Architect agent scaffolding — tool use, multi-step reasoning, memory, sandbox execution — tailored to customer workflows\n\n - Configure and launch training runs on Lab, iterating on reward functions, rollout strategies, and evaluation criteria\n\n - Serve as the technical lead for engagements end-to-end: from discovery through deployed, improved models\n\n\nPLATFORM FEEDBACK & ECOSYSTEM\n\n - Identify repeatable patterns from customer engagements and codify them into reference implementations, templates, and documentation\n\n - Serve as the voice of the customer internally, shaping the roadmap for Lab, verifiers, the Environments Hub, and training infrastructure\n\n - Build high-quality examples and \"recipes\" that make it easy for new customers and open-source contributors to extend the stack\n\n - Contribute to technical content (blog posts, tutorials, case studies) that demonstrates real-world platform usage\n\n\nAPPLIED RESEARCH & EXPERIMENTATION\n\n - Develop novel evaluation methodologies for agentic behavior — multi-step reasoning, tool use correctness, recovery from failure, long-horizon task completion\n\n - Prototype and iterate on agent harnesses for real-world tasks: code generation, workflow automation, document processing, and more\n\n - Experiment with reward design, rubric construction, and environment shaping to improve training signal quality\n\n - Stay current on the frontier of agentic AI, evals, and post-training methods, and bring that knowledge directly into customer work\n\n\nWHAT WE'RE LOOKING FOR\n\n - Deep hands-on experience building, evaluating, or deploying LLM-based agents in the past 1–2 years — you've seen what breaks in production and know what good evals look like\n\n - Strong intuition for evaluation design: you can look at a customer's agent and quickly identify what to measure, how to construct a rubric, and where the reward signal is weak\n\n - Working understanding of RL and post-training concepts (GRPO, RLHF, reward modeling, SFT) — you don't need to have written a trainer from scratch, but you should understand what the knobs do and why they matter\n\n - Strong Python skills and comfort with the modern AI stack (Hugging Face, inference engines, agent frameworks)\n\n - Experience in a customer-facing or consulting-adjacent technical role, or as a technical founder — you're comfortable in a room with a customer's engineering team figuring out what to build\n\n - Excellent written and verbal communication — you can write a clear environment spec, a compelling case study, and a useful Slack message to a frustrated customer\n\n - High agency and comfort with ambiguity. You don't wait for specs; you scope the problem, ship a solution, and iterate\n\n\n\n\nNICE-TO-HAVES\n\n - Experience with agent frameworks and tooling (DSPy, LangGraph, MCP, Stagehand, browser automation)\n\n - Experience building or running LLM evaluation pipelines at scale (benchmarks, synthetic data generation, model grading)\n\n - Research experience — publications, open-source contributions, or benchmarks in ML/RL/agents\n\n - Familiarity with sandbox/code execution environments for agent evaluation\n\n - Web programming experience (React, TypeScript, Next.js) for building demos and customer-facing tooling\n   \n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $150-300k + equity incentives\n\n - Flexible Work (San Francisco or hybrid-remote)\n\n - Visa Sponsorship & relocation support\n\n - Professional Development budget\n\n - Team Off-sites & conference attendance\n\n\n\nGROWTH OPPORTUNITY\n\nYou’ll join a mission-driven team working at the frontier of open, superintelligence infra. In this role, you’ll have the opportunity to:\n\n - Shape the evolution of agent-driven solutions—from research breakthroughs to production systems used by real customers.\n\n - Collaborate with leading researchers, engineers, and partners pushing the boundaries of RL and post-training.\n\n - Grow with a fast-moving organization where your contributions directly influence both the technical direction and the broader AI ecosystem.\n\nIf you’re excited to move fast, build boldly, and help define how agentic AI is developed and deployed, we’d love to hear from you.\n\n\n\nReady to build the open superintelligence infrastructure of tomorrow?\nApply now to help us make powerful, open AGI accessible to everyone."},{"id":"05e4b76b-2570-4c89-baf2-9833fff7378f","title":"Research Engineer - RL Infrastructure ","department":"Research","team":"Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-07-08T18:43:53.584+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/05e4b76b-2570-4c89-baf2-9833fff7378f","applyUrl":"https://jobs.ashbyhq.com/primeintellect/05e4b76b-2570-4c89-baf2-9833fff7378f/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">We train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models — compute, large-scale RL, environments, sandboxes, evals, and deployment.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2></h2><h2>What You’ll Work On</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and optimize the systems infrastructure behind large-scale RL and distributed training workloads by contributing to our <a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://github.com/PrimeIntellect-ai/prime-rl\">prime-rl</a> framework.</p></li><li><p style=\"min-height:1.5em\">Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.</p></li><li><p style=\"min-height:1.5em\">Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.</p></li><li><p style=\"min-height:1.5em\">Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.</p></li><li><p style=\"min-height:1.5em\">Help shape the architecture of our RL training stack, including async rollout and post-training systems.</p></li><li><p style=\"min-height:1.5em\">Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.</p></li><li><p style=\"min-height:1.5em\">Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.</p></li><li><p style=\"min-height:1.5em\">Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.</p></li></ul><h2></h2><h2>You May Be a Fit If You Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.</p></li><li><p style=\"min-height:1.5em\">Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.</p></li><li><p style=\"min-height:1.5em\">Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.</p></li><li><p style=\"min-height:1.5em\">Strong understanding of GPU architecture, profiling, and performance debugging.</p></li><li><p style=\"min-height:1.5em\">Ability to identify bottlenecks across the stack and drive improvements from first principles.</p></li><li><p style=\"min-height:1.5em\">Comfort working in a fast-moving environment with ambiguous problems and high ownership.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Especially Exciting</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience writing or optimizing CUDA / Triton kernels.</p></li><li><p style=\"min-height:1.5em\">Experience with compiler or runtime optimization for ML systems.</p></li><li><p style=\"min-height:1.5em\">Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.</p></li><li><p style=\"min-height:1.5em\">Experience with multi-node GPU clusters and high-performance networking.</p></li><li><p style=\"min-height:1.5em\">Contributions to open-source ML systems or infrastructure projects.</p></li><li><p style=\"min-height:1.5em\">Interest in publishing technical work or sharing insights through engineering blogs and technical writing.</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Why This Role Matters</h2><p style=\"min-height:1.5em\">The next frontier in AI will not be unlocked by models alone. It will be unlocked by systems that let those models train faster, adapt continuously, and operate across real environments at scale.</p><p style=\"min-height:1.5em\">That infrastructure does not exist yet in the form the world needs.</p><p style=\"min-height:1.5em\">We’re building it.</p><p style=\"min-height:1.5em\"></p><h2>Benefits &amp; Perks</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150-350k, plus equity.</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangements, with the option to work remotely or in person from our San Francisco office.</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support for international candidates.</p></li><li><p style=\"min-height:1.5em\">Quarterly team offsites, hackathons, conferences, and learning opportunities.</p></li><li><p style=\"min-height:1.5em\">A deeply technical, high-agency team working on infrastructure for open superintelligence.</p></li></ul><p style=\"min-height:1.5em\">If you’re excited about building the systems foundation for frontier-scale RL and open superintelligence, we’d love to hear from you.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nWe train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models — compute, large-scale RL, environments, sandboxes, evals, and deployment.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\n\nWHAT YOU’LL WORK ON\n\n - Build and optimize the systems infrastructure behind large-scale RL and distributed training workloads by contributing to our prime-rl https://github.com/PrimeIntellect-ai/prime-rl framework.\n\n - Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.\n\n - Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.\n\n - Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.\n\n - Help shape the architecture of our RL training stack, including async rollout and post-training systems.\n\n - Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.\n\n - Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.\n\n - Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.\n\n\n\n\n\nYOU MAY BE A FIT IF YOU HAVE\n\n - Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.\n\n - Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.\n\n - Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.\n\n - Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.\n\n - Strong understanding of GPU architecture, profiling, and performance debugging.\n\n - Ability to identify bottlenecks across the stack and drive improvements from first principles.\n\n - Comfort working in a fast-moving environment with ambiguous problems and high ownership.\n\n\n\n\nESPECIALLY EXCITING\n\n - Experience writing or optimizing CUDA / Triton kernels.\n\n - Experience with compiler or runtime optimization for ML systems.\n\n - Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.\n\n - Experience with multi-node GPU clusters and high-performance networking.\n\n - Contributions to open-source ML systems or infrastructure projects.\n\n - Interest in publishing technical work or sharing insights through engineering blogs and technical writing.\n\n\n\n\nWHY THIS ROLE MATTERS\n\nThe next frontier in AI will not be unlocked by models alone. It will be unlocked by systems that let those models train faster, adapt continuously, and operate across real environments at scale.\n\nThat infrastructure does not exist yet in the form the world needs.\n\nWe’re building it.\n\n\n\n\nBENEFITS & PERKS\n\n - Cash Compensation Range of $150-350k, plus equity.\n\n - Flexible work arrangements, with the option to work remotely or in person from our San Francisco office.\n\n - Visa sponsorship and relocation support for international candidates.\n\n - Quarterly team offsites, hackathons, conferences, and learning opportunities.\n\n - A deeply technical, high-agency team working on infrastructure for open superintelligence.\n\nIf you’re excited about building the systems foundation for frontier-scale RL and open superintelligence, we’d love to hear from you."},{"id":"597d302f-9aee-45fd-a726-92aa2fad64eb","title":"Head of Marketing","department":"Growth","team":"Growth","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:42:08.019+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/597d302f-9aee-45fd-a726-92aa2fad64eb","applyUrl":"https://jobs.ashbyhq.com/primeintellect/597d302f-9aee-45fd-a726-92aa2fad64eb/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2><br />Your Role</h2><p style=\"min-height:1.5em\">As Head of Marketing &amp; Developer Relations, you'll own how Prime Intellect shows up in the world — the story we tell, the community we build, and how developers and researchers discover, adopt, and champion our platform. You'll shape our brand, run high-signal campaigns and launches, grow our developer community, and build the content engine that makes Prime Intellect the default starting point for RL infrastructure. This is a high-leverage role combining narrative craft, technical credibility, and community instinct — ideal for someone who can move fluidly between writing a launch post, scoping a conference strategy, and shipping a developer tutorial.</p><h2><br />Responsibilities</h2><h3>Brand &amp; Narrative</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Define and evolve Prime Intellect's brand positioning, voice, and visual identity across all channels.</p></li><li><p style=\"min-height:1.5em\">Translate deeply technical capabilities (async RL, distributed training, agentic post-training) into clear, compelling market narratives.</p></li><li><p style=\"min-height:1.5em\">Own messaging frameworks for product launches, fundraise announcements, research releases, and partnership news.</p></li></ul><h3>Developer Relations &amp; Community</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and lead the DevRel function — creating programs, content, and experiences that drive developer adoption and loyalty.</p></li><li><p style=\"min-height:1.5em\">Grow and engage our open-source community (Environments Hub, prime-rl, Verifiers) through tutorials, office hours, hackathons, and contributor programs.</p></li><li><p style=\"min-height:1.5em\">Develop and maintain developer documentation, quickstarts, and onboarding flows in close partnership with Product and Engineering.</p></li><li><p style=\"min-height:1.5em\">Represent Prime Intellect at conferences, meetups, and on podcasts — and identify opportunities for the founding team to do the same.</p></li></ul><h3>Content &amp; Thought Leadership</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build a content engine spanning technical blog posts, research digests, case studies, video content, and social media.</p></li><li><p style=\"min-height:1.5em\">Partner with Research to translate frontier work (Recursive Language Models, INTELLECT model series, CLaaS) into high-signal public content.</p></li><li><p style=\"min-height:1.5em\">Develop a thought leadership program that positions Prime Intellect's founders and researchers as key voices in open AI infrastructure.</p></li></ul><h3>Campaigns &amp; Growth</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Plan and execute product launches, research releases, and community events that generate developer awareness and adoption.</p></li><li><p style=\"min-height:1.5em\">Run growth experiments across channels — organic social, paid, SEO, email, partnerships — and build measurement systems to track what works.</p></li><li><p style=\"min-height:1.5em\">Own top-of-funnel metrics: developer signups, community engagement, content reach, and brand awareness.</p></li><li><p style=\"min-height:1.5em\">Partner with Sales/GTM to ensure marketing-generated demand converts into pipeline and design-partner relationships.</p></li></ul><h3>Marketing Operations</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and manage the marketing tech stack (analytics, CMS, email, social scheduling, attribution).</p></li><li><p style=\"min-height:1.5em\">Establish reporting cadence for marketing KPIs and campaign performance.</p></li><li><p style=\"min-height:1.5em\">Manage external agencies, freelancers, and contractors as needed for design, video, and content production.</p></li></ul><h2><br />What We're Looking For</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">5+ years in marketing, developer relations, or developer marketing at a B2B infrastructure, open-source, or developer-tools company.</p></li><li><p style=\"min-height:1.5em\">Deep technical fluency — you can credibly discuss GPUs, RL training loops, model architectures, and API design with engineers and researchers.</p></li><li><p style=\"min-height:1.5em\">Proven track record building developer communities and running high-impact product launches.</p></li><li><p style=\"min-height:1.5em\">Strong writer and storyteller who can produce or direct content that resonates with both technical and business audiences.</p></li><li><p style=\"min-height:1.5em\">Analytical and experiment-driven — comfortable with attribution models, funnel metrics, and growth experiments.</p></li><li><p style=\"min-height:1.5em\">Experience building small, high-performing teams from scratch in fast-moving environments.</p></li></ul><h3>Bonus</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Hands-on experience with AI/ML infrastructure, cloud platforms, or open-source ML tooling.</p></li><li><p style=\"min-height:1.5em\">Existing presence and credibility in the AI research or infrastructure community (blog, Twitter/X, conference talks).</p></li><li><p style=\"min-height:1.5em\">Experience with open-source community building and contributor growth programs.</p></li><li><p style=\"min-height:1.5em\">Early-stage operator mindset — bias for building playbooks, not inheriting them.</p></li></ul><h2><br />What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $150–300k + equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible Work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa Sponsorship &amp; relocation support</p></li><li><p style=\"min-height:1.5em\">Professional Development budget</p></li><li><p style=\"min-height:1.5em\">Team Off-sites &amp; conference attendance</p></li><li><p style=\"min-height:1.5em\">Opportunity to shape open AI infrastructure at Prime Intellect</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nYOUR ROLE\n\nAs Head of Marketing & Developer Relations, you'll own how Prime Intellect shows up in the world — the story we tell, the community we build, and how developers and researchers discover, adopt, and champion our platform. You'll shape our brand, run high-signal campaigns and launches, grow our developer community, and build the content engine that makes Prime Intellect the default starting point for RL infrastructure. This is a high-leverage role combining narrative craft, technical credibility, and community instinct — ideal for someone who can move fluidly between writing a launch post, scoping a conference strategy, and shipping a developer tutorial.\n\n\n\nRESPONSIBILITIES\n\n\nBRAND & NARRATIVE\n\n - Define and evolve Prime Intellect's brand positioning, voice, and visual identity across all channels.\n\n - Translate deeply technical capabilities (async RL, distributed training, agentic post-training) into clear, compelling market narratives.\n\n - Own messaging frameworks for product launches, fundraise announcements, research releases, and partnership news.\n\n\nDEVELOPER RELATIONS & COMMUNITY\n\n - Build and lead the DevRel function — creating programs, content, and experiences that drive developer adoption and loyalty.\n\n - Grow and engage our open-source community (Environments Hub, prime-rl, Verifiers) through tutorials, office hours, hackathons, and contributor programs.\n\n - Develop and maintain developer documentation, quickstarts, and onboarding flows in close partnership with Product and Engineering.\n\n - Represent Prime Intellect at conferences, meetups, and on podcasts — and identify opportunities for the founding team to do the same.\n\n\nCONTENT & THOUGHT LEADERSHIP\n\n - Build a content engine spanning technical blog posts, research digests, case studies, video content, and social media.\n\n - Partner with Research to translate frontier work (Recursive Language Models, INTELLECT model series, CLaaS) into high-signal public content.\n\n - Develop a thought leadership program that positions Prime Intellect's founders and researchers as key voices in open AI infrastructure.\n\n\nCAMPAIGNS & GROWTH\n\n - Plan and execute product launches, research releases, and community events that generate developer awareness and adoption.\n\n - Run growth experiments across channels — organic social, paid, SEO, email, partnerships — and build measurement systems to track what works.\n\n - Own top-of-funnel metrics: developer signups, community engagement, content reach, and brand awareness.\n\n - Partner with Sales/GTM to ensure marketing-generated demand converts into pipeline and design-partner relationships.\n\n\nMARKETING OPERATIONS\n\n - Build and manage the marketing tech stack (analytics, CMS, email, social scheduling, attribution).\n\n - Establish reporting cadence for marketing KPIs and campaign performance.\n\n - Manage external agencies, freelancers, and contractors as needed for design, video, and content production.\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - 5+ years in marketing, developer relations, or developer marketing at a B2B infrastructure, open-source, or developer-tools company.\n\n - Deep technical fluency — you can credibly discuss GPUs, RL training loops, model architectures, and API design with engineers and researchers.\n\n - Proven track record building developer communities and running high-impact product launches.\n\n - Strong writer and storyteller who can produce or direct content that resonates with both technical and business audiences.\n\n - Analytical and experiment-driven — comfortable with attribution models, funnel metrics, and growth experiments.\n\n - Experience building small, high-performing teams from scratch in fast-moving environments.\n\n\nBONUS\n\n - Hands-on experience with AI/ML infrastructure, cloud platforms, or open-source ML tooling.\n\n - Existing presence and credibility in the AI research or infrastructure community (blog, Twitter/X, conference talks).\n\n - Experience with open-source community building and contributor growth programs.\n\n - Early-stage operator mindset — bias for building playbooks, not inheriting them.\n\n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $150–300k + equity incentives\n\n - Flexible Work (remote or San Francisco)\n\n - Visa Sponsorship & relocation support\n\n - Professional Development budget\n\n - Team Off-sites & conference attendance\n\n - Opportunity to shape open AI infrastructure at Prime Intellect"},{"id":"fb497090-0336-45b2-b802-9d34d8758d06","title":"Member of Technical Staff - Security","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:33:48.099+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/fb497090-0336-45b2-b802-9d34d8758d06","applyUrl":"https://jobs.ashbyhq.com/primeintellect/fb497090-0336-45b2-b802-9d34d8758d06/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"><br /></p><h2>Role Impact</h2><p style=\"min-height:1.5em\">Security is the single highest-stakes function at Prime Intellect. Our customers — from frontier AI labs to enterprises — trust us with their most valuable assets: proprietary models, training data, and the compute that powers them. This role owns the security posture of everything we ship: the hosted RL training platform, distributed GPU infrastructure, liquid compute marketplace, and all customer-facing surfaces.</p><p style=\"min-height:1.5em\">You'll be the first dedicated security hire and will define how we think about security as a company — from threat modeling and secure architecture to incident response and compliance. You'll work directly with engineering, research, and leadership to embed security into every layer of the stack, and you'll manage relationships with external penetration testers and security auditors to continuously validate our defenses.</p><p style=\"min-height:1.5em\"></p><h2>Core Technical Responsibilities</h2><h3>Preventive Security &amp; Secure Architecture</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own threat modeling across our entire surface area: multi-tenant training infrastructure, sandboxed execution environments, API surfaces, and internal tooling</p></li><li><p style=\"min-height:1.5em\">Design and implement zero-trust networking, identity, and access control across distributed GPU clusters and cloud infrastructure</p></li><li><p style=\"min-height:1.5em\">Build secure-by-default patterns for our platform engineers — auth, secrets management, supply chain integrity, container hardening</p></li><li><p style=\"min-height:1.5em\">Architect tenant isolation and data boundary enforcement for hosted RL training workloads (customers run arbitrary code in our environments)</p></li></ul><h3>AI-Native Security</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Develop security frameworks specific to AI infrastructure: model weight protection, training data isolation, checkpoint integrity, gradient privacy</p></li><li><p style=\"min-height:1.5em\">Secure the RL training loop end-to-end — from environment execution in sandboxes to reward signal verification and model artifact storage</p></li><li><p style=\"min-height:1.5em\">Build detection and prevention for AI-specific attack vectors: prompt injection across agentic pipelines, model exfiltration, adversarial environment manipulation</p></li></ul><h3>Offensive Security &amp; External Engagements</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Scope, manage, and run point on external penetration tests across our platform, hosted training infrastructure, and liquid compute layer</p></li><li><p style=\"min-height:1.5em\">Build and maintain an internal red-teaming practice — automated and manual — targeting our most critical systems</p></li><li><p style=\"min-height:1.5em\">Drive vulnerability management: triage, remediation SLAs, and root cause analysis</p></li></ul><h3>Detection, Response &amp; Observability</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build security monitoring and alerting across infrastructure (distributed clusters, Kubernetes, cloud) and application layers</p></li><li><p style=\"min-height:1.5em\">Implement runtime security for containerized training workloads and sandboxed environments</p></li><li><p style=\"min-height:1.5em\">Own incident response — build the playbooks, run the drills, lead the post-mortems</p></li><li><p style=\"min-height:1.5em\">Design audit logging and forensic capability across all customer-facing systems</p></li></ul><h3>Compliance &amp; Customer Trust</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Drive SOC 2 Type II readiness and other compliance frameworks required by enterprise customers</p></li><li><p style=\"min-height:1.5em\">Own the security narrative for customer-facing materials — questionnaires, architecture reviews, trust documentation</p></li><li><p style=\"min-height:1.5em\">Partner with GTM to unblock enterprise deals that depend on security posture</p></li></ul><h2>Technical Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">5+ years in security engineering, infrastructure security, or offensive security roles — ideally at companies operating multi-tenant cloud or compute infrastructure</p></li><li><p style=\"min-height:1.5em\">Deep experience with cloud security (GCP preferred), Kubernetes security, and container runtime hardening</p></li><li><p style=\"min-height:1.5em\">Hands-on ability to read, write, and audit code in Python and Rust (or strong systems-level language)</p></li><li><p style=\"min-height:1.5em\">Experience with network security in distributed systems — service mesh, mTLS, network segmentation across heterogeneous hardware</p></li><li><p style=\"min-height:1.5em\">Proven track record managing external penetration tests and translating findings into engineering action</p></li><li><p style=\"min-height:1.5em\">Strong fundamentals in cryptography, identity/access management, and secure software development lifecycle</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience securing GPU infrastructure or ML training pipelines</p></li><li><p style=\"min-height:1.5em\">Background in offensive security — CTFs, bug bounties, red team engagements</p></li><li><p style=\"min-height:1.5em\">Familiarity with AI-specific threat models (model extraction, training data poisoning, sandbox escape)</p></li><li><p style=\"min-height:1.5em\">Experience building security programs from scratch at a high-growth startup</p></li><li><p style=\"min-height:1.5em\">SOC 2, ISO 27001, or FedRAMP compliance experience</p></li><li><p style=\"min-height:1.5em\">Open-source security tooling contributions</p></li><li><p style=\"min-height:1.5em\">Familiarity with eBPF, Falco, or similar runtime security tools</p></li></ul><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $180-350k+ with significant equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangement (remote or San Francisco office)</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">Opportunity to shape the future of decentralized AI development</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll be the foundational security hire at a company where security is existential — not a checkbox. As we scale to support frontier AI labs and enterprises running their most critical training workloads on our platform, you'll build the security org from the ground up and have direct influence on company strategy.</p><p style=\"min-height:1.5em\">We value intensity and ownership over credentials. If you've built security programs at infrastructure companies, broken into systems professionally, or have deep conviction about how AI infrastructure should be secured — we want to talk.</p><p style=\"min-height:1.5em\">Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\n\nROLE IMPACT\n\nSecurity is the single highest-stakes function at Prime Intellect. Our customers — from frontier AI labs to enterprises — trust us with their most valuable assets: proprietary models, training data, and the compute that powers them. This role owns the security posture of everything we ship: the hosted RL training platform, distributed GPU infrastructure, liquid compute marketplace, and all customer-facing surfaces.\n\nYou'll be the first dedicated security hire and will define how we think about security as a company — from threat modeling and secure architecture to incident response and compliance. You'll work directly with engineering, research, and leadership to embed security into every layer of the stack, and you'll manage relationships with external penetration testers and security auditors to continuously validate our defenses.\n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n\nPREVENTIVE SECURITY & SECURE ARCHITECTURE\n\n - Own threat modeling across our entire surface area: multi-tenant training infrastructure, sandboxed execution environments, API surfaces, and internal tooling\n\n - Design and implement zero-trust networking, identity, and access control across distributed GPU clusters and cloud infrastructure\n\n - Build secure-by-default patterns for our platform engineers — auth, secrets management, supply chain integrity, container hardening\n\n - Architect tenant isolation and data boundary enforcement for hosted RL training workloads (customers run arbitrary code in our environments)\n\n\nAI-NATIVE SECURITY\n\n - Develop security frameworks specific to AI infrastructure: model weight protection, training data isolation, checkpoint integrity, gradient privacy\n\n - Secure the RL training loop end-to-end — from environment execution in sandboxes to reward signal verification and model artifact storage\n\n - Build detection and prevention for AI-specific attack vectors: prompt injection across agentic pipelines, model exfiltration, adversarial environment manipulation\n\n\nOFFENSIVE SECURITY & EXTERNAL ENGAGEMENTS\n\n - Scope, manage, and run point on external penetration tests across our platform, hosted training infrastructure, and liquid compute layer\n\n - Build and maintain an internal red-teaming practice — automated and manual — targeting our most critical systems\n\n - Drive vulnerability management: triage, remediation SLAs, and root cause analysis\n\n\nDETECTION, RESPONSE & OBSERVABILITY\n\n - Build security monitoring and alerting across infrastructure (distributed clusters, Kubernetes, cloud) and application layers\n\n - Implement runtime security for containerized training workloads and sandboxed environments\n\n - Own incident response — build the playbooks, run the drills, lead the post-mortems\n\n - Design audit logging and forensic capability across all customer-facing systems\n\n\nCOMPLIANCE & CUSTOMER TRUST\n\n - Drive SOC 2 Type II readiness and other compliance frameworks required by enterprise customers\n\n - Own the security narrative for customer-facing materials — questionnaires, architecture reviews, trust documentation\n\n - Partner with GTM to unblock enterprise deals that depend on security posture\n\n\nTECHNICAL REQUIREMENTS\n\n - 5+ years in security engineering, infrastructure security, or offensive security roles — ideally at companies operating multi-tenant cloud or compute infrastructure\n\n - Deep experience with cloud security (GCP preferred), Kubernetes security, and container runtime hardening\n\n - Hands-on ability to read, write, and audit code in Python and Rust (or strong systems-level language)\n\n - Experience with network security in distributed systems — service mesh, mTLS, network segmentation across heterogeneous hardware\n\n - Proven track record managing external penetration tests and translating findings into engineering action\n\n - Strong fundamentals in cryptography, identity/access management, and secure software development lifecycle\n\n\nNICE TO HAVE\n\n - Experience securing GPU infrastructure or ML training pipelines\n\n - Background in offensive security — CTFs, bug bounties, red team engagements\n\n - Familiarity with AI-specific threat models (model extraction, training data poisoning, sandbox escape)\n\n - Experience building security programs from scratch at a high-growth startup\n\n - SOC 2, ISO 27001, or FedRAMP compliance experience\n\n - Open-source security tooling contributions\n\n - Familiarity with eBPF, Falco, or similar runtime security tools\n\n\nWHAT WE OFFER\n\n - Cash Compensation Range of $180-350k+ with significant equity incentives\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n - Opportunity to shape the future of decentralized AI development\n\n\nGROWTH OPPORTUNITY\n\nYou'll be the foundational security hire at a company where security is existential — not a checkbox. As we scale to support frontier AI labs and enterprises running their most critical training workloads on our platform, you'll build the security org from the ground up and have direct influence on company strategy.\n\nWe value intensity and ownership over credentials. If you've built security programs at infrastructure companies, broken into systems professionally, or have deep conviction about how AI infrastructure should be secured — we want to talk.\n\nReady to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone."},{"id":"d523340c-9914-4b86-828a-147c9ada94d3","title":"Solutions Architect - AI Infrastructure","department":"Compute / Finance","team":"Compute / Finance","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:36:17.454+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/d523340c-9914-4b86-828a-147c9ada94d3","applyUrl":"https://jobs.ashbyhq.com/primeintellect/d523340c-9914-4b86-828a-147c9ada94d3/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h1>Role Impact</h1><p style=\"min-height:1.5em\">This role sits at the intersection of customer success, technical operations, and AI infrastructure delivery. You will work directly with customers to help them onboard, deploy, and scale on Prime Intellect infrastructure, while also building the internal systems, workflows, and automation that make that experience scalable over time.</p><p style=\"min-height:1.5em\">Beyond supporting individual accounts, this person will help define how Prime Intellect serves sophisticated technical customers: turning high-touch support and deployment work into repeatable processes, better tooling, and durable operational leverage.</p><p style=\"min-height:1.5em\"></p><h1>What You’ll Do</h1><p style=\"min-height:1.5em\"></p><h2>Customer Success &amp; Account Ownership</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Serve as a primary point of contact for customers running AI workloads on our infrastructure</p></li><li><p style=\"min-height:1.5em\">Own customer onboarding and deployment coordination from post-sale through production readiness</p></li><li><p style=\"min-height:1.5em\">Build trusted relationships with customer teams and proactively manage issues, risks, and escalations</p></li><li><p style=\"min-height:1.5em\">Partner with engineering and operations to ensure customer needs are translated clearly into internal action</p></li></ul><h2>Systems, Tooling &amp; Operational Scale</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build and improve the internal systems that support customer onboarding, deployment tracking, escalation management, and account health</p></li><li><p style=\"min-height:1.5em\">Identify repetitive manual workflows and turn them into streamlined processes, tooling, or automation</p></li><li><p style=\"min-height:1.5em\">Help define the operating cadence, support infrastructure, and service model for managing technical customer accounts at scale</p></li><li><p style=\"min-height:1.5em\">Create structure where none exists today, improving both customer experience and internal efficiency as the business grows</p></li></ul><h2>Commercial &amp; Cross-Functional Execution</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Track billing, contract milestones, renewals, and other key account workflows</p></li><li><p style=\"min-height:1.5em\">Maintain visibility into deployment timelines, infrastructure commitments, and customer-specific requirements</p></li><li><p style=\"min-height:1.5em\">Coordinate across customers, finance, engineering, and leadership to keep accounts running smoothly end-to-end</p></li></ul><p style=\"min-height:1.5em\"></p><h1>Requirements</h1><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">2–5 years of experience in customer success, technical account management, operations, or a similar cross-functional role</p></li><li><p style=\"min-height:1.5em\">Strong interest in AI, GPU infrastructure, cloud systems, or technical products serving sophisticated customers</p></li><li><p style=\"min-height:1.5em\">Comfortable working directly with customers and internal technical teams</p></li><li><p style=\"min-height:1.5em\">Highly organized, detail-oriented, and able to manage multiple workstreams at once</p></li><li><p style=\"min-height:1.5em\">Strong written and verbal communication skills</p></li><li><p style=\"min-height:1.5em\">High ownership and willingness to operate flexibly when customer needs require urgency</p></li><li><p style=\"min-height:1.5em\">Energized by building processes from the ground up in a fast-moving environment</p></li></ul><p style=\"min-height:1.5em\"></p><h1>Nice-to-Haves</h1><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with infrastructure, cloud, DevOps, or enterprise technical products</p></li><li><p style=\"min-height:1.5em\">Familiarity with SLAs, support operations, billing, procurement, or contract administration</p></li><li><p style=\"min-height:1.5em\">Exposure to AI/ML infrastructure, model training environments, or GPU-based products</p></li><li><p style=\"min-height:1.5em\">Experience in startups or high-growth environments</p></li></ul><p style=\"min-height:1.5em\"></p><h1>What We Offer</h1><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">$200-275k Cash compensation + equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible work environment</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conference attendance</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nROLE IMPACT\n\nThis role sits at the intersection of customer success, technical operations, and AI infrastructure delivery. You will work directly with customers to help them onboard, deploy, and scale on Prime Intellect infrastructure, while also building the internal systems, workflows, and automation that make that experience scalable over time.\n\nBeyond supporting individual accounts, this person will help define how Prime Intellect serves sophisticated technical customers: turning high-touch support and deployment work into repeatable processes, better tooling, and durable operational leverage.\n\n\n\n\nWHAT YOU’LL DO\n\n\n\n\nCUSTOMER SUCCESS & ACCOUNT OWNERSHIP\n\n - Serve as a primary point of contact for customers running AI workloads on our infrastructure\n\n - Own customer onboarding and deployment coordination from post-sale through production readiness\n\n - Build trusted relationships with customer teams and proactively manage issues, risks, and escalations\n\n - Partner with engineering and operations to ensure customer needs are translated clearly into internal action\n\n\nSYSTEMS, TOOLING & OPERATIONAL SCALE\n\n - Build and improve the internal systems that support customer onboarding, deployment tracking, escalation management, and account health\n\n - Identify repetitive manual workflows and turn them into streamlined processes, tooling, or automation\n\n - Help define the operating cadence, support infrastructure, and service model for managing technical customer accounts at scale\n\n - Create structure where none exists today, improving both customer experience and internal efficiency as the business grows\n\n\nCOMMERCIAL & CROSS-FUNCTIONAL EXECUTION\n\n - Track billing, contract milestones, renewals, and other key account workflows\n\n - Maintain visibility into deployment timelines, infrastructure commitments, and customer-specific requirements\n\n - Coordinate across customers, finance, engineering, and leadership to keep accounts running smoothly end-to-end\n\n\n\n\nREQUIREMENTS\n\n - 2–5 years of experience in customer success, technical account management, operations, or a similar cross-functional role\n\n - Strong interest in AI, GPU infrastructure, cloud systems, or technical products serving sophisticated customers\n\n - Comfortable working directly with customers and internal technical teams\n\n - Highly organized, detail-oriented, and able to manage multiple workstreams at once\n\n - Strong written and verbal communication skills\n\n - High ownership and willingness to operate flexibly when customer needs require urgency\n\n - Energized by building processes from the ground up in a fast-moving environment\n\n\n\n\nNICE-TO-HAVES\n\n - Experience with infrastructure, cloud, DevOps, or enterprise technical products\n\n - Familiarity with SLAs, support operations, billing, procurement, or contract administration\n\n - Exposure to AI/ML infrastructure, model training environments, or GPU-based products\n\n - Experience in startups or high-growth environments\n\n\n\n\nWHAT WE OFFER\n\n - $200-275k Cash compensation + equity incentives\n\n - Flexible work environment\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conference attendance"},{"id":"0457e19e-927b-41e9-beb4-d6dd3a676b9e","title":"Head of Compute","department":"Compute / Finance","team":"Compute / Finance","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:35:44.774+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/0457e19e-927b-41e9-beb4-d6dd3a676b9e","applyUrl":"https://jobs.ashbyhq.com/primeintellect/0457e19e-927b-41e9-beb4-d6dd3a676b9e/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><strong>Your Role</strong></h2><p style=\"min-height:1.5em\">You will own compute at Prime Intellect - the sourcing, economics, contracting, and strategic positioning of the GPU supply that powers everything we train, serve, and sell.</p><p style=\"min-height:1.5em\">This is one of the most consequential roles at the company, and one of the most consequential compute roles in the industry. Compute is our product, and compute is the constraint that shapes what the open AI ecosystem can do. Every frontier lab is fighting for the same GPUs; your job is to make sure the open ecosystem has a leading seat at the table.</p><p style=\"min-height:1.5em\">The decisions you make will shape the industry. Which neoclouds get the capital and commitments to scale. Which geographies become meaningful compute hubs. Which hardware generations get broad access versus staying locked inside closed labs. Which open models are economically possible to train and serve. You'll co-design the compute layer of the open model ecosystem alongside our research and engineering teams — deciding, together, what we train, on what, where, and at what cost structure.</p><p style=\"min-height:1.5em\">You'll work directly with leadership team and founders of the neoclouds reshaping global compute, and with the research and engineering teams pushing the frontier of open post-training. You'll structure the commercial relationships that define the next several years of AI infrastructure, get first access to the latest generations of accelerators as they come online, and build the financial and operational architecture that turns a fragmented global supply market into Prime Intellect's durable advantage.</p><p style=\"min-height:1.5em\">You need to be as comfortable modeling the unit economics of a three-year GB200 commitment against a volatile spot market as you are sitting with our research team to understand what an upcoming training run actually needs, or negotiating a nine-figure reserved capacity agreement with neocloud leadership.</p><p style=\"min-height:1.5em\"></p><h2><strong>Responsibilities</strong></h2><p style=\"min-height:1.5em\"><strong>Compute Strategy &amp; Economics</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own the economics of compute end-to-end: the unit economics of every contract, the margin architecture across training and inference products, the long-term P&amp;L consequences of today's supply bets</p></li><li><p style=\"min-height:1.5em\">Partner with Finance and leadership on capital strategy — how much to commit, to whom, for how long, on which hardware, with what balance sheet exposure</p></li><li><p style=\"min-height:1.5em\">Build the frameworks that turn supply decisions into clear financial outcomes, and that let us make multi-hundred-million-dollar bets with conviction under uncertainty</p></li><li><p style=\"min-height:1.5em\">Shape the commercial architecture of the open compute ecosystem: how committed capacity, spot markets, credit structures, and partner economics fit together</p></li></ul><p style=\"min-height:1.5em\"><strong>Sourcing &amp; Contracting</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own end-to-end procurement of GPU capacity globally — across hyperscalers, tier-one neoclouds, regional operators, and emerging providers in North America, Europe, the Middle East, and Asia</p></li><li><p style=\"min-height:1.5em\">Negotiate and close reserved capacity agreements, spot and burst arrangements, MSAs, DPAs, and order forms at nine- and ten-figure scale</p></li><li><p style=\"min-height:1.5em\">Secure early access to the latest generations of accelerators (B200, GB200, and what comes next) — in the quantities we need, before our competitors</p></li><li><p style=\"min-height:1.5em\">Build and maintain the senior relationships that make Prime Intellect the partner of choice for providers deciding where to allocate scarce capacity</p></li></ul><p style=\"min-height:1.5em\"><strong>Co-Design with Research &amp; Engineering</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Work closely with our research team to translate training roadmaps, RL workloads, and open model ambitions into concrete compute requirements — and back the other way, to surface what's possible given the supply we can secure</p></li><li><p style=\"min-height:1.5em\">Partner with Engineering on acceptance testing, goodput validation, and the technical qualification of new providers and hardware</p></li><li><p style=\"min-height:1.5em\">Sit at the table where the biggest calls get made: which open models we train, which customers we serve, which bets are worth the capital</p></li></ul><p style=\"min-height:1.5em\"><strong>Market Intelligence &amp; Positioning</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Track pricing, availability, and provider dynamics continuously across every major global market</p></li><li><p style=\"min-height:1.5em\">Serve as the internal source of truth on the compute market — who's credible, who's mispriced, where supply is about to tighten, which providers will still exist in 18 months, where the next wave of capacity is coming online</p></li><li><p style=\"min-height:1.5em\">Advise leadership on the strategic bets that define the company: which accelerators, which providers, which geographies, which contract structures, which moments to lean in hard</p></li></ul><p style=\"min-height:1.5em\"></p><h2><strong>What We're Looking For</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong business and financial instincts — you think natively in unit economics, margin structure, and capital allocation, and you can model the long-term P&amp;L consequences of complex supply decisions</p></li><li><p style=\"min-height:1.5em\">Deep fluency in the global AI compute market: you know the providers, the hardware generations and their real tradeoffs, the pricing dynamics, and where the market is going over the next 12–24 months</p></li><li><p style=\"min-height:1.5em\">Enough technical understanding to be dangerous — you can push back on a vendor's spec sheet, read a cluster topology diagram, understand why two nominally identical clusters deliver different goodput, and have a real conversation with researchers about what their workloads need</p></li><li><p style=\"min-height:1.5em\">Serious commercial chops: you've negotiated and closed contracts at meaningful scale, know how to find and use leverage, and understand how deal structure drives downstream economics</p></li><li><p style=\"min-height:1.5em\">Comfortable operating at the intersection of finance, commercial, product, and engineering — and translating fluently between all of them</p></li><li><p style=\"min-height:1.5em\">High ownership: you see gaps and build the fix before anyone asks</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster</p></li></ul><p style=\"min-height:1.5em\"></p><h2><strong>What We Offer</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Competitive Cash Compensation + meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nYou will own compute at Prime Intellect - the sourcing, economics, contracting, and strategic positioning of the GPU supply that powers everything we train, serve, and sell.\n\nThis is one of the most consequential roles at the company, and one of the most consequential compute roles in the industry. Compute is our product, and compute is the constraint that shapes what the open AI ecosystem can do. Every frontier lab is fighting for the same GPUs; your job is to make sure the open ecosystem has a leading seat at the table.\n\nThe decisions you make will shape the industry. Which neoclouds get the capital and commitments to scale. Which geographies become meaningful compute hubs. Which hardware generations get broad access versus staying locked inside closed labs. Which open models are economically possible to train and serve. You'll co-design the compute layer of the open model ecosystem alongside our research and engineering teams — deciding, together, what we train, on what, where, and at what cost structure.\n\nYou'll work directly with leadership team and founders of the neoclouds reshaping global compute, and with the research and engineering teams pushing the frontier of open post-training. You'll structure the commercial relationships that define the next several years of AI infrastructure, get first access to the latest generations of accelerators as they come online, and build the financial and operational architecture that turns a fragmented global supply market into Prime Intellect's durable advantage.\n\nYou need to be as comfortable modeling the unit economics of a three-year GB200 commitment against a volatile spot market as you are sitting with our research team to understand what an upcoming training run actually needs, or negotiating a nine-figure reserved capacity agreement with neocloud leadership.\n\n\n\n\nRESPONSIBILITIES\n\nCompute Strategy & Economics\n\n - Own the economics of compute end-to-end: the unit economics of every contract, the margin architecture across training and inference products, the long-term P&L consequences of today's supply bets\n\n - Partner with Finance and leadership on capital strategy — how much to commit, to whom, for how long, on which hardware, with what balance sheet exposure\n\n - Build the frameworks that turn supply decisions into clear financial outcomes, and that let us make multi-hundred-million-dollar bets with conviction under uncertainty\n\n - Shape the commercial architecture of the open compute ecosystem: how committed capacity, spot markets, credit structures, and partner economics fit together\n\nSourcing & Contracting\n\n - Own end-to-end procurement of GPU capacity globally — across hyperscalers, tier-one neoclouds, regional operators, and emerging providers in North America, Europe, the Middle East, and Asia\n\n - Negotiate and close reserved capacity agreements, spot and burst arrangements, MSAs, DPAs, and order forms at nine- and ten-figure scale\n\n - Secure early access to the latest generations of accelerators (B200, GB200, and what comes next) — in the quantities we need, before our competitors\n\n - Build and maintain the senior relationships that make Prime Intellect the partner of choice for providers deciding where to allocate scarce capacity\n\nCo-Design with Research & Engineering\n\n - Work closely with our research team to translate training roadmaps, RL workloads, and open model ambitions into concrete compute requirements — and back the other way, to surface what's possible given the supply we can secure\n\n - Partner with Engineering on acceptance testing, goodput validation, and the technical qualification of new providers and hardware\n\n - Sit at the table where the biggest calls get made: which open models we train, which customers we serve, which bets are worth the capital\n\nMarket Intelligence & Positioning\n\n - Track pricing, availability, and provider dynamics continuously across every major global market\n\n - Serve as the internal source of truth on the compute market — who's credible, who's mispriced, where supply is about to tighten, which providers will still exist in 18 months, where the next wave of capacity is coming online\n\n - Advise leadership on the strategic bets that define the company: which accelerators, which providers, which geographies, which contract structures, which moments to lean in hard\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - Strong business and financial instincts — you think natively in unit economics, margin structure, and capital allocation, and you can model the long-term P&L consequences of complex supply decisions\n\n - Deep fluency in the global AI compute market: you know the providers, the hardware generations and their real tradeoffs, the pricing dynamics, and where the market is going over the next 12–24 months\n\n - Enough technical understanding to be dangerous — you can push back on a vendor's spec sheet, read a cluster topology diagram, understand why two nominally identical clusters deliver different goodput, and have a real conversation with researchers about what their workloads need\n\n - Serious commercial chops: you've negotiated and closed contracts at meaningful scale, know how to find and use leverage, and understand how deal structure drives downstream economics\n\n - Comfortable operating at the intersection of finance, commercial, product, and engineering — and translating fluently between all of them\n\n - High ownership: you see gaps and build the fix before anyone asks\n\n - AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster\n\n\n\n\nWHAT WE OFFER\n\n - Competitive Cash Compensation + meaningful equity\n\n - Flexible work (remote or San Francisco)\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"26c41d54-f823-4aac-8fdf-4e78fc760184","title":"Member of Technical Staff - Sandbox Platform","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-09-23T17:20:12.976+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/26c41d54-f823-4aac-8fdf-4e78fc760184","applyUrl":"https://jobs.ashbyhq.com/primeintellect/26c41d54-f823-4aac-8fdf-4e78fc760184/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.  </p><p style=\"min-height:1.5em\"></p><h2>Core Technical Responsibilities</h2><p style=\"min-height:1.5em\">You'll build the distributed control plane and node-level runtime behind our sandbox platform: placing workloads across bare-metal workers, launching secure microVMs, and making the entire lifecycle fast, efficient, and resilient to failure.</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build the control plane that places sandbox workloads efficiently across bare-metal CPU and GPU workers.</p></li><li><p style=\"min-height:1.5em\">Build node-level execution systems that launch and supervise secure microVMs, coordinate storage and networking, and take sandboxes from assignment to ready execution.</p></li><li><p style=\"min-height:1.5em\">Own the sandbox product surface, including its APIs, SDK, and CLI, and evolve it to support reinforcement learning and agentic workflows at scale.</p></li><li><p style=\"min-height:1.5em\">Work closely with research, applied research, customers, and the broader engineering team to take problems from discovery through design, implementation, and production adoption. </p></li></ul><p style=\"min-height:1.5em\"></p><h2>Technical Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">You have 5+ years of experience building production distributed systems from the ground up.</p></li><li><p style=\"min-height:1.5em\">You have strong systems programming experience. Production Go is a major advantage; Rust, C++, or comparable systems-language experience is also valued.</p></li><li><p style=\"min-height:1.5em\">You are a high-agency engineer who can lead the design and implementation of high-performance, fault-tolerant systems.</p></li><li><p style=\"min-height:1.5em\">You have strong Linux systems fundamentals and depth in at least one of virtualization, networking, storage, or workload isolation.</p></li><li><p style=\"min-height:1.5em\">You enjoy going deep on systems performance, whether the bottleneck is memory behavior, concurrency, networking, or resource utilization.</p></li><li><p style=\"min-height:1.5em\">You have built, deployed, and operated production systems at scale. </p></li></ul><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation of $150-300k with significant equity incentives</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangements, with our San Francisco office preferred and remote work possible for exceptional candidates</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">A professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">The opportunity to shape core infrastructure for frontier AI research </p></li></ul><p style=\"min-height:1.5em\"></p><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll work alongside experienced engineers and researchers building core infrastructure for frontier AI research. You'll shape the sandbox platform that powers demanding reinforcement learning, evaluation, and agentic workloads, with opportunities to contribute to open-source infrastructure.</p><p style=\"min-height:1.5em\">On a small, high-ownership team, you'll help set technical direction and engineering practices while moving quickly from decisions to shipped systems.</p><p style=\"min-height:1.5em\">We value deep systems expertise and customer obsession. If you want to build foundational infrastructure from the control plane down to the node runtime, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and help build the systems behind the next generation of AI research.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.  \n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\nYou'll build the distributed control plane and node-level runtime behind our sandbox platform: placing workloads across bare-metal workers, launching secure microVMs, and making the entire lifecycle fast, efficient, and resilient to failure.\n\n - Build the control plane that places sandbox workloads efficiently across bare-metal CPU and GPU workers.\n\n - Build node-level execution systems that launch and supervise secure microVMs, coordinate storage and networking, and take sandboxes from assignment to ready execution.\n\n - Own the sandbox product surface, including its APIs, SDK, and CLI, and evolve it to support reinforcement learning and agentic workflows at scale.\n\n - Work closely with research, applied research, customers, and the broader engineering team to take problems from discovery through design, implementation, and production adoption. \n\n\n\n\nTECHNICAL REQUIREMENTS\n\n - You have 5+ years of experience building production distributed systems from the ground up.\n\n - You have strong systems programming experience. Production Go is a major advantage; Rust, C++, or comparable systems-language experience is also valued.\n\n - You are a high-agency engineer who can lead the design and implementation of high-performance, fault-tolerant systems.\n\n - You have strong Linux systems fundamentals and depth in at least one of virtualization, networking, storage, or workload isolation.\n\n - You enjoy going deep on systems performance, whether the bottleneck is memory behavior, concurrency, networking, or resource utilization.\n\n - You have built, deployed, and operated production systems at scale. \n\n\n\n\nWHAT WE OFFER\n\n - Cash compensation of $150-300k with significant equity incentives\n\n - Flexible work arrangements, with our San Francisco office preferred and remote work possible for exceptional candidates\n\n - Full visa sponsorship and relocation support\n\n - A professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n - The opportunity to shape core infrastructure for frontier AI research \n\n\n\n\nGROWTH OPPORTUNITY\n\nYou'll work alongside experienced engineers and researchers building core infrastructure for frontier AI research. You'll shape the sandbox platform that powers demanding reinforcement learning, evaluation, and agentic workloads, with opportunities to contribute to open-source infrastructure.\n\nOn a small, high-ownership team, you'll help set technical direction and engineering practices while moving quickly from decisions to shipped systems.\n\nWe value deep systems expertise and customer obsession. If you want to build foundational infrastructure from the control plane down to the node runtime, we want to talk to you.\n\nApply now and help build the systems behind the next generation of AI research."},{"id":"d70f38c9-ae8e-4252-933a-666cb900e3b4","title":"Technical Account Manager - AI Infrastructure","department":"Compute / Finance","team":"Compute / Finance","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:36:01.490+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/d70f38c9-ae8e-4252-933a-666cb900e3b4","applyUrl":"https://jobs.ashbyhq.com/primeintellect/d70f38c9-ae8e-4252-933a-666cb900e3b4/application","descriptionHtml":"<h2>Technical Account Manager </h2><h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Your Role</strong></p><p style=\"min-height:1.5em\">Prime Intellect serves some of the most sophisticated AI teams in the world that depend on our compute and infrastructure to train and deploy production AI systems. The Customer Success Manager is the person who makes sure those customers succeed, scale, and keep building with us.</p><p style=\"min-height:1.5em\">This is not a traditional Customer Success role. Our customers run large-scale training jobs, scale inference workloads against real production traffic, and depend on cluster reliability and performance the way most companies depend on their cloud provider. The work spans the technical and the commercial — you'll be reading Grafana dashboards and discussing cluster performance with a customer's ML infrastructure team in the morning, and partnering with Sales on a capacity expansion in the afternoon.</p><p style=\"min-height:1.5em\">You'll own a portfolio of enterprise customers end-to-end and build the relationships that make Prime Intellect the partner of choice for their AI infrastructure.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Responsibilities</strong></p><p style=\"min-height:1.5em\"><strong>Customer Ownership</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health</p></li><li><p style=\"min-height:1.5em\">Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership</p></li><li><p style=\"min-height:1.5em\">Drive customer outcomes: faster time-to-value on first workloads, smooth scaling as their usage grows, and meaningful expansion as their AI ambitions expand</p></li></ul><p style=\"min-height:1.5em\"><strong>Technical Partnership</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Understand each customer's training and inference workloads at a real technical level — what models they're training, what infrastructure they need, what their performance bottlenecks are</p></li><li><p style=\"min-height:1.5em\">Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration</p></li><li><p style=\"min-height:1.5em\">Translate customer needs into clear, prioritized feedback for our Engineering and Product teams</p></li></ul><p style=\"min-height:1.5em\"><strong>Expansion &amp; Renewals</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Identify expansion opportunities ahead of the customer — anticipate scaling needs, surface new use cases, drive adoption of new products (Lab, Inference, additional compute capacity)</p></li><li><p style=\"min-height:1.5em\">Partner with Sales on renewal conversations and growth motions</p></li><li><p style=\"min-height:1.5em\">Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute</p></li></ul><p style=\"min-height:1.5em\"><strong>Operational Excellence</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Serve as the first line for customer-facing operational issues — usage questions, capacity changes, SLA tracking, incident communications</p></li><li><p style=\"min-height:1.5em\">Build the cross-functional connective tissue between Sales, Engineering, Finance, and customers</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>What We're Looking For</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3–6 years in Customer Success, Technical Account Management, Solutions Engineering, or adjacent roles at infrastructure, cloud, or AI/ML companies</p></li><li><p style=\"min-height:1.5em\">Strong technical fluency — comfortable reading dashboards, discussing infrastructure architecture, and engaging with customer engineering teams without a translator</p></li><li><p style=\"min-height:1.5em\">Strong commercial instincts — you understand that Customer Success is a revenue function, not a support function, and you can drive real expansion alongside technical outcomes</p></li><li><p style=\"min-height:1.5em\">Deep customer empathy combined with high judgment — you advocate for customers internally while making the calls that are right for the business</p></li><li><p style=\"min-height:1.5em\">Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa</p></li><li><p style=\"min-height:1.5em\">High ownership — you see gaps and build the fix before anyone asks</p></li><li><p style=\"min-height:1.5em\">Comfortable in ambiguity and speed; this market doesn't slow down</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Direct experience at a cloud provider, AI infrastructure company, or compute marketplace</p></li><li><p style=\"min-height:1.5em\">Familiarity with GPU economics, training and inference workloads, or compute consumption patterns</p></li><li><p style=\"min-height:1.5em\">Background as a TAM or Solutions Architect at a hyperscaler (AWS, GCP, Azure) or specialized cloud provider</p></li><li><p style=\"min-height:1.5em\">Working knowledge of usage-based pricing, capacity commitments, and consumption-based contracts</p></li><li><p style=\"min-height:1.5em\">You've been an early Customer Success hire at a high-growth company</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>What We Offer</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $160,000 – $200,000 + meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"TECHNICAL ACCOUNT MANAGER \n\n\nOWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nYour Role\n\nPrime Intellect serves some of the most sophisticated AI teams in the world that depend on our compute and infrastructure to train and deploy production AI systems. The Customer Success Manager is the person who makes sure those customers succeed, scale, and keep building with us.\n\nThis is not a traditional Customer Success role. Our customers run large-scale training jobs, scale inference workloads against real production traffic, and depend on cluster reliability and performance the way most companies depend on their cloud provider. The work spans the technical and the commercial — you'll be reading Grafana dashboards and discussing cluster performance with a customer's ML infrastructure team in the morning, and partnering with Sales on a capacity expansion in the afternoon.\n\nYou'll own a portfolio of enterprise customers end-to-end and build the relationships that make Prime Intellect the partner of choice for their AI infrastructure.\n\n\n\nResponsibilities\n\nCustomer Ownership\n\n - Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health\n\n - Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership\n\n - Drive customer outcomes: faster time-to-value on first workloads, smooth scaling as their usage grows, and meaningful expansion as their AI ambitions expand\n\nTechnical Partnership\n\n - Understand each customer's training and inference workloads at a real technical level — what models they're training, what infrastructure they need, what their performance bottlenecks are\n\n - Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration\n\n - Translate customer needs into clear, prioritized feedback for our Engineering and Product teams\n\nExpansion & Renewals\n\n - Identify expansion opportunities ahead of the customer — anticipate scaling needs, surface new use cases, drive adoption of new products (Lab, Inference, additional compute capacity)\n\n - Partner with Sales on renewal conversations and growth motions\n\n - Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute\n\nOperational Excellence\n\n - Serve as the first line for customer-facing operational issues — usage questions, capacity changes, SLA tracking, incident communications\n\n - Build the cross-functional connective tissue between Sales, Engineering, Finance, and customers\n\n\n\nWhat We're Looking For\n\n - 3–6 years in Customer Success, Technical Account Management, Solutions Engineering, or adjacent roles at infrastructure, cloud, or AI/ML companies\n\n - Strong technical fluency — comfortable reading dashboards, discussing infrastructure architecture, and engaging with customer engineering teams without a translator\n\n - Strong commercial instincts — you understand that Customer Success is a revenue function, not a support function, and you can drive real expansion alongside technical outcomes\n\n - Deep customer empathy combined with high judgment — you advocate for customers internally while making the calls that are right for the business\n\n - Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa\n\n - High ownership — you see gaps and build the fix before anyone asks\n\n - Comfortable in ambiguity and speed; this market doesn't slow down\n\n - AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster\n\n\n\nBonus:\n\n - Direct experience at a cloud provider, AI infrastructure company, or compute marketplace\n\n - Familiarity with GPU economics, training and inference workloads, or compute consumption patterns\n\n - Background as a TAM or Solutions Architect at a hyperscaler (AWS, GCP, Azure) or specialized cloud provider\n\n - Working knowledge of usage-based pricing, capacity commitments, and consumption-based contracts\n\n - You've been an early Customer Success hire at a high-growth company\n\n\n\nWhat We Offer\n\n - Cash Compensation Range of $160,000 – $200,000 + meaningful equity\n\n - Flexible work (remote or San Francisco)\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"5366fc55-df00-4c2c-b389-8850a9393840","title":"Compute Intelligence Engineer","department":"Compute / Finance","team":"Compute / Finance","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:35:28.204+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/5366fc55-df00-4c2c-b389-8850a9393840","applyUrl":"https://jobs.ashbyhq.com/primeintellect/5366fc55-df00-4c2c-b389-8850a9393840/application","descriptionHtml":"<h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"><strong>Your Role</strong></p><p style=\"min-height:1.5em\">Compute is the foundational input of everything Prime Intellect does — and right now, the picture of our compute supply, demand, and economics lives across spreadsheets, partner conversations, and people's heads. This role changes that.</p><p style=\"min-height:1.5em\">As Compute Intelligence Engineer, you'll build the data infrastructure and intelligence platform that gives the entire company a live, accurate picture of our compute: what we have, what's coming online, where our bottlenecks are, and how supply maps to demand. This is a hands-on data engineering build — you'll stand up the warehouse, write the pipelines that pull from our compute telemetry, billing systems, partner data, and CRM, model that data into a clean and trustworthy source of truth, and turn it into dashboards and a queryable layer the whole company relies on.</p><p style=\"min-height:1.5em\">This is a builder-first role with a clear business purpose. You won't be building data infrastructure for its own sake — you'll be building the system that lets our Compute Partnerships team, Growth team, and Research team operate from the same source of truth. When Growth needs to know what capacity is coming online next quarter, when Compute Partnerships needs to understand our utilization against commitments, when Research needs to scale a training run — the platform you build is what they'll turn to.</p><p style=\"min-height:1.5em\">You'll be early in this seat, and the foundations you lay will be the data backbone the company scales on.</p><p style=\"min-height:1.5em\"><strong>Responsibilities</strong></p><p style=\"min-height:1.5em\"><strong>Build the Compute Intelligence Platform</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Stand up Prime Intellect's data warehouse (Snowflake, BigQuery, or equivalent) and the pipelines that feed it — compute telemetry, billing and usage data, partner and supply data, CRM, and financial systems</p></li><li><p style=\"min-height:1.5em\">Build the data models and transformations (dbt or equivalent) that turn raw data into a clean, queryable, trustworthy source of truth</p></li><li><p style=\"min-height:1.5em\">Build dashboards and reporting that give the company a live picture of compute supply, demand, utilization, upcoming capacity, and bottlenecks</p></li><li><p style=\"min-height:1.5em\">Build a queryable, AI-accessible layer on top of the warehouse so teams across the company can answer their own questions without going through a data analyst</p></li></ul><p style=\"min-height:1.5em\"><strong>Supply &amp; Demand Intelligence</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build the data systems that track our compute supply end-to-end: what we have, what's committed, what's coming online, and what's utilized vs. idle</p></li><li><p style=\"min-height:1.5em\">Develop the views and models that surface where our bottlenecks are — and make upcoming supply legible to the teams that depend on it</p></li><li><p style=\"min-height:1.5em\">Connect supply data to demand signals so the company can see, in one place, how capacity maps to what we're selling and building</p></li></ul><p style=\"min-height:1.5em\"><strong>Cross-Functional Enablement</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Serve as the data backbone connecting Compute Partnerships, Growth, and Research — building the systems that let them operate from shared, accurate information</p></li><li><p style=\"min-height:1.5em\">Partner with Growth on understanding upcoming supply and how it maps to what they can sell</p></li><li><p style=\"min-height:1.5em\">Partner with Compute Partnerships on utilization, commitments, and supply tracking</p></li><li><p style=\"min-height:1.5em\">Partner with Research on scaling needs and capacity planning</p></li></ul><p style=\"min-height:1.5em\"><strong>Operational Reliability</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build pipelines and systems that run unattended, stay in sync, and fail gracefully</p></li><li><p style=\"min-height:1.5em\">Establish the data quality, documentation, and infrastructure standards that let the data layer scale with the company</p></li><li><p style=\"min-height:1.5em\">Partner with Engineering on shared infrastructure, security, and data standards</p></li></ul><p style=\"min-height:1.5em\"><strong>What We're Looking For</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles where you've built data infrastructure that served real business outcomes</p></li><li><p style=\"min-height:1.5em\">Strong technical skills: comfortable building and maintaining data warehouses, writing production-quality pipelines (Python, SQL), modeling data (dbt or equivalent), and connecting disparate systems via APIs</p></li><li><p style=\"min-height:1.5em\">Experience with modern data stack tooling — Snowflake / BigQuery / Databricks, dbt, orchestration (Airflow, Dagster, etc.), and BI/dashboarding tools</p></li><li><p style=\"min-height:1.5em\">A builder's instinct paired with business judgment — you don't just build what's asked; you understand the business well enough to build the right thing</p></li><li><p style=\"min-height:1.5em\">Comfortable being the data backbone for cross-functional teams — translating between business needs and the systems that serve them</p></li><li><p style=\"min-height:1.5em\">Familiarity with modern AI tooling and an interest in building AI-accessible data layers (natural-language querying, LLM-powered analytics) that let non-technical teams self-serve</p></li><li><p style=\"min-height:1.5em\">High ownership — you see gaps and build the fix before anyone asks</p></li><li><p style=\"min-height:1.5em\">Comfortable in ambiguity and speed; you'll be defining what the data layer looks like from scratch</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience as an early data hire who built a company's data infrastructure from scratch</p></li><li><p style=\"min-height:1.5em\">Familiarity with GPU economics, compute infrastructure, cloud telemetry, or AI/ML workloads</p></li><li><p style=\"min-height:1.5em\">Background in GTM engineering, growth engineering, or revenue/operations data</p></li><li><p style=\"min-height:1.5em\">Experience building LLM-powered or natural-language data interfaces</p></li><li><p style=\"min-height:1.5em\">Working knowledge of usage-based / consumption-based business models and the data they generate</p></li></ul><p style=\"min-height:1.5em\"><strong>What We Offer</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash Compensation Range of $225-300k + meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work (remote or San Francisco)</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\nYour Role\n\nCompute is the foundational input of everything Prime Intellect does — and right now, the picture of our compute supply, demand, and economics lives across spreadsheets, partner conversations, and people's heads. This role changes that.\n\nAs Compute Intelligence Engineer, you'll build the data infrastructure and intelligence platform that gives the entire company a live, accurate picture of our compute: what we have, what's coming online, where our bottlenecks are, and how supply maps to demand. This is a hands-on data engineering build — you'll stand up the warehouse, write the pipelines that pull from our compute telemetry, billing systems, partner data, and CRM, model that data into a clean and trustworthy source of truth, and turn it into dashboards and a queryable layer the whole company relies on.\n\nThis is a builder-first role with a clear business purpose. You won't be building data infrastructure for its own sake — you'll be building the system that lets our Compute Partnerships team, Growth team, and Research team operate from the same source of truth. When Growth needs to know what capacity is coming online next quarter, when Compute Partnerships needs to understand our utilization against commitments, when Research needs to scale a training run — the platform you build is what they'll turn to.\n\nYou'll be early in this seat, and the foundations you lay will be the data backbone the company scales on.\n\nResponsibilities\n\nBuild the Compute Intelligence Platform\n\n - Stand up Prime Intellect's data warehouse (Snowflake, BigQuery, or equivalent) and the pipelines that feed it — compute telemetry, billing and usage data, partner and supply data, CRM, and financial systems\n\n - Build the data models and transformations (dbt or equivalent) that turn raw data into a clean, queryable, trustworthy source of truth\n\n - Build dashboards and reporting that give the company a live picture of compute supply, demand, utilization, upcoming capacity, and bottlenecks\n\n - Build a queryable, AI-accessible layer on top of the warehouse so teams across the company can answer their own questions without going through a data analyst\n\nSupply & Demand Intelligence\n\n - Build the data systems that track our compute supply end-to-end: what we have, what's committed, what's coming online, and what's utilized vs. idle\n\n - Develop the views and models that surface where our bottlenecks are — and make upcoming supply legible to the teams that depend on it\n\n - Connect supply data to demand signals so the company can see, in one place, how capacity maps to what we're selling and building\n\nCross-Functional Enablement\n\n - Serve as the data backbone connecting Compute Partnerships, Growth, and Research — building the systems that let them operate from shared, accurate information\n\n - Partner with Growth on understanding upcoming supply and how it maps to what they can sell\n\n - Partner with Compute Partnerships on utilization, commitments, and supply tracking\n\n - Partner with Research on scaling needs and capacity planning\n\nOperational Reliability\n\n - Build pipelines and systems that run unattended, stay in sync, and fail gracefully\n\n - Establish the data quality, documentation, and infrastructure standards that let the data layer scale with the company\n\n - Partner with Engineering on shared infrastructure, security, and data standards\n\nWhat We're Looking For\n\n - 3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles where you've built data infrastructure that served real business outcomes\n\n - Strong technical skills: comfortable building and maintaining data warehouses, writing production-quality pipelines (Python, SQL), modeling data (dbt or equivalent), and connecting disparate systems via APIs\n\n - Experience with modern data stack tooling — Snowflake / BigQuery / Databricks, dbt, orchestration (Airflow, Dagster, etc.), and BI/dashboarding tools\n\n - A builder's instinct paired with business judgment — you don't just build what's asked; you understand the business well enough to build the right thing\n\n - Comfortable being the data backbone for cross-functional teams — translating between business needs and the systems that serve them\n\n - Familiarity with modern AI tooling and an interest in building AI-accessible data layers (natural-language querying, LLM-powered analytics) that let non-technical teams self-serve\n\n - High ownership — you see gaps and build the fix before anyone asks\n\n - Comfortable in ambiguity and speed; you'll be defining what the data layer looks like from scratch\n\n - AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster\n\nBonus:\n\n - Experience as an early data hire who built a company's data infrastructure from scratch\n\n - Familiarity with GPU economics, compute infrastructure, cloud telemetry, or AI/ML workloads\n\n - Background in GTM engineering, growth engineering, or revenue/operations data\n\n - Experience building LLM-powered or natural-language data interfaces\n\n - Working knowledge of usage-based / consumption-based business models and the data they generate\n\nWhat We Offer\n\n - Cash Compensation Range of $225-300k + meaningful equity\n\n - Flexible work (remote or San Francisco)\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"657b85c3-2f1a-4015-9692-5bd0389cfe4b","title":"Applied AI: Product Strategy & Revenue Lead","department":"Growth","team":"Growth","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:33:30.661+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/657b85c3-2f1a-4015-9692-5bd0389cfe4b","applyUrl":"https://jobs.ashbyhq.com/primeintellect/657b85c3-2f1a-4015-9692-5bd0389cfe4b/application","descriptionHtml":"<h1>Applied AI Product Strategy &amp; Revenue Lead<br /></h1><h2><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><br />The Role</h2><p style=\"min-height:1.5em\">This is not a traditional sales role. It is not a traditional product role. It is not a traditional solutions engineering role.</p><p style=\"min-height:1.5em\">You will help define how Prime Intellect turns frontier post-training infrastructure into a product customers can understand, buy, deploy, and expand.</p><p style=\"min-height:1.5em\">Today, the hardest part of the business is not selling raw compute. It is refining the product, customer motion, and technical wedge together with Applied Research, Product, Engineering, and the customer. We are selling something much more complex and much more valuable than GPUs: the ability for customers to build their own lab — environments, evals, verifiers, agents, training runs, and deployment loops that compound over time.</p><p style=\"min-height:1.5em\">You will own that messy middle.</p><p style=\"min-height:1.5em\">You will work directly with customers, the CEO, GTM leadership, Applied Research, and Engineering to translate ambiguous customer pain into a concrete product strategy, technical scope, commercial proposal, and path to revenue. You will help us figure out where the product is ready, where it needs to be shaped, what the customer actually wants, and how to turn early traction into repeatable motion.</p><p style=\"min-height:1.5em\">This is a role for someone who wants to be in the room where a new category is being created.</p><h2><br />What You’ll Own</h2><h3>Customer-to-Product Translation</h3><p style=\"min-height:1.5em\">You will work with frontier AI labs, fast-growing AI startups, and enterprise AI teams to understand what they are trying to build, where their current stack breaks, and how Prime Intellect can become the infrastructure layer underneath their post-training and agent workflows.</p><p style=\"min-height:1.5em\">You will turn vague, high-stakes customer conversations into clear technical and commercial strategy:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">What is the customer actually trying to improve?</p></li><li><p style=\"min-height:1.5em\">Is the wedge compute, evals, environments, sandboxes, managed RL, SFT, inference, or a full-stack workflow?</p></li><li><p style=\"min-height:1.5em\">What should Applied Research build or prototype?</p></li><li><p style=\"min-height:1.5em\">What needs to be packaged as product?</p></li><li><p style=\"min-height:1.5em\">What should be in scope for a POC versus a long-term deployment?</p></li><li><p style=\"min-height:1.5em\">What is the fastest path to a strong yes?</p></li></ul><h3>Pre-PMF Product Strategy</h3><p style=\"min-height:1.5em\">You will help shape Prime Intellect’s product motion before every part of the playbook is obvious.</p><p style=\"min-height:1.5em\">That means identifying patterns across customer conversations, building repeatable narratives, defining packaging, sharpening use cases, and helping the team understand which customer asks are one-off noise versus signs of a massive market.</p><p style=\"min-height:1.5em\">You will help answer questions like:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">How do we explain Lab to different customer segments?</p></li><li><p style=\"min-height:1.5em\">Which customer workflows should become reference architectures?</p></li><li><p style=\"min-height:1.5em\">What should we productize versus deliver as managed work?</p></li><li><p style=\"min-height:1.5em\">Where is the strongest wedge for enterprise customers?</p></li><li><p style=\"min-height:1.5em\">Which signals show that a customer is ready for managed post-training?</p></li><li><p style=\"min-height:1.5em\">How do we turn Applied Research work into revenue without diluting the research agenda?</p></li></ul><h3>Revenue Ownership</h3><p style=\"min-height:1.5em\">You will own high-value customer opportunities from first serious conversation through qualification, scoping, proposal, POC, procurement, and expansion.</p><p style=\"min-height:1.5em\">You will not be measured on activity. You will be measured on whether the most important customers move.</p><p style=\"min-height:1.5em\">This includes:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Running discovery with technical and executive stakeholders</p></li><li><p style=\"min-height:1.5em\">Building the business case and technical wedge</p></li><li><p style=\"min-height:1.5em\">Owning account strategy with leadership</p></li><li><p style=\"min-height:1.5em\">Drafting proposals, scopes, and commercial structures</p></li><li><p style=\"min-height:1.5em\">Coordinating internal workstreams across Applied Research, Product, Engineering, Legal, and Finance</p></li><li><p style=\"min-height:1.5em\">Creating momentum through ambiguity</p></li><li><p style=\"min-height:1.5em\">Turning early deployments into expansion and long-term platform revenue</p></li></ul><h3>Applied Research Partnership</h3><p style=\"min-height:1.5em\">You will work extremely closely with Applied Research.</p><p style=\"min-height:1.5em\">The best version of this role has enough technical taste to understand where an RL/post-training workflow is real, where a customer is hand-waving, and where a sharp Applied Research prototype could unlock a major deal.</p><p style=\"min-height:1.5em\">You will help Applied Research prioritize customer-facing work by bringing signal from the field:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Which evals matter?</p></li><li><p style=\"min-height:1.5em\">Which environments should we build?</p></li><li><p style=\"min-height:1.5em\">Which agents or workflows are most commercially valuable?</p></li><li><p style=\"min-height:1.5em\">Which technical demos will change the customer’s mind?</p></li><li><p style=\"min-height:1.5em\">Which customer problems are actually research problems in disguise?</p></li></ul><h3>Category Creation</h3><p style=\"min-height:1.5em\">The market understands compute. It does not yet fully understand full-stack post-training infrastructure.</p><p style=\"min-height:1.5em\">You will help write the playbook.</p><p style=\"min-height:1.5em\">You will contribute to positioning, sales narratives, customer decks, case studies, reference architectures, launch moments, and internal strategy. You should be able to turn raw customer conversations into crisp language the entire company can use.</p><h2><br />What We’re Looking For</h2><p style=\"min-height:1.5em\">We are looking for exceptional generalists with rare taste across AI, product, customers, and commercial strategy.</p><p style=\"min-height:1.5em\">You might come from:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Technical GTM at a frontier AI, infra, devtools, or enterprise software company</p></li><li><p style=\"min-height:1.5em\">Founder or early operator experience at an AI startup</p></li><li><p style=\"min-height:1.5em\">Product or strategy at a highly technical company</p></li><li><p style=\"min-height:1.5em\">Forward-deployed engineering, solutions, or applied AI work</p></li><li><p style=\"min-height:1.5em\">Investing, venture, or strategic finance with deep AI infrastructure exposure</p></li><li><p style=\"min-height:1.5em\">Research-adjacent roles where you worked directly with customers or product teams</p></li></ul><p style=\"min-height:1.5em\">You should have:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong product and commercial judgment</p></li><li><p style=\"min-height:1.5em\">Ability to understand technical products quickly</p></li><li><p style=\"min-height:1.5em\">Excellent written communication</p></li><li><p style=\"min-height:1.5em\">High agency and comfort with ambiguity</p></li><li><p style=\"min-height:1.5em\">Taste for what makes a customer problem real</p></li><li><p style=\"min-height:1.5em\">Ability to work with researchers, engineers, executives, and operators</p></li><li><p style=\"min-height:1.5em\">Sharp instincts around enterprise buying, POCs, procurement, and expansion</p></li><li><p style=\"min-height:1.5em\">Obsession with AI, post-training, agents, evals, and infrastructure</p></li><li><p style=\"min-height:1.5em\">Ability to create structure where none exists</p></li></ul><p style=\"min-height:1.5em\">You do not need to be a researcher, but you should be technical enough to earn trust with researchers and customers.</p><p style=\"min-height:1.5em\">You do not need to be a traditional salesperson, but you should be commercially intense enough to close.</p><p style=\"min-height:1.5em\">You do not need to be a PM, but you should have strong product taste.</p><h2><br />Bonus Points</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with RL, SFT, evals, agent frameworks, or LLM post-training</p></li><li><p style=\"min-height:1.5em\">Experience selling or deploying infrastructure, AI platforms, devtools, or enterprise AI products</p></li><li><p style=\"min-height:1.5em\">Experience working with frontier AI labs, model companies, or infra-heavy startups</p></li><li><p style=\"min-height:1.5em\">Ability to write excellent customer-facing decks, memos, proposals, and launch narratives</p></li><li><p style=\"min-height:1.5em\">Strong network across AI startups, research labs, or enterprise AI teams</p></li><li><p style=\"min-height:1.5em\">Founder mentality and willingness to do unglamorous work to win</p></li></ul><h2><br />Why This Role</h2><p style=\"min-height:1.5em\">Most GTM roles ask you to sell a product someone else already defined.</p><p style=\"min-height:1.5em\">This role asks you to help define the product, the market, the motion, and the revenue engine at the same time.</p><p style=\"min-height:1.5em\">You will work on the hardest commercial and product questions at one of the fastest-growing companies in AI infrastructure. You will sit close to customers building real AI systems, researchers pushing the frontier of post-training, and leadership making company-defining decisions.</p><p style=\"min-height:1.5em\">If you want a clean playbook, this is not the role.</p><p style=\"min-height:1.5em\">If you want to help invent the playbook for how frontier AI infrastructure gets built, packaged, sold, deployed, and scaled, this is the role.</p><h2><br />What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Competitive cash compensation and meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work in San Francisco or hybrid-remote</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul><h2><br />Ready to Build the Commercial Engine for Open Superintelligence?</h2><p style=\"min-height:1.5em\">Apply to help Prime Intellect turn frontier post-training infrastructure into the product, platform, and customer motion that powers the next generation of AI systems.</p>","descriptionPlain":"APPLIED AI PRODUCT STRATEGY & REVENUE LEAD\n\n\n\nOWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\n\nTHE ROLE\n\nThis is not a traditional sales role. It is not a traditional product role. It is not a traditional solutions engineering role.\n\nYou will help define how Prime Intellect turns frontier post-training infrastructure into a product customers can understand, buy, deploy, and expand.\n\nToday, the hardest part of the business is not selling raw compute. It is refining the product, customer motion, and technical wedge together with Applied Research, Product, Engineering, and the customer. We are selling something much more complex and much more valuable than GPUs: the ability for customers to build their own lab — environments, evals, verifiers, agents, training runs, and deployment loops that compound over time.\n\nYou will own that messy middle.\n\nYou will work directly with customers, the CEO, GTM leadership, Applied Research, and Engineering to translate ambiguous customer pain into a concrete product strategy, technical scope, commercial proposal, and path to revenue. You will help us figure out where the product is ready, where it needs to be shaped, what the customer actually wants, and how to turn early traction into repeatable motion.\n\nThis is a role for someone who wants to be in the room where a new category is being created.\n\n\n\nWHAT YOU’LL OWN\n\n\nCUSTOMER-TO-PRODUCT TRANSLATION\n\nYou will work with frontier AI labs, fast-growing AI startups, and enterprise AI teams to understand what they are trying to build, where their current stack breaks, and how Prime Intellect can become the infrastructure layer underneath their post-training and agent workflows.\n\nYou will turn vague, high-stakes customer conversations into clear technical and commercial strategy:\n\n - What is the customer actually trying to improve?\n\n - Is the wedge compute, evals, environments, sandboxes, managed RL, SFT, inference, or a full-stack workflow?\n\n - What should Applied Research build or prototype?\n\n - What needs to be packaged as product?\n\n - What should be in scope for a POC versus a long-term deployment?\n\n - What is the fastest path to a strong yes?\n\n\nPRE-PMF PRODUCT STRATEGY\n\nYou will help shape Prime Intellect’s product motion before every part of the playbook is obvious.\n\nThat means identifying patterns across customer conversations, building repeatable narratives, defining packaging, sharpening use cases, and helping the team understand which customer asks are one-off noise versus signs of a massive market.\n\nYou will help answer questions like:\n\n - How do we explain Lab to different customer segments?\n\n - Which customer workflows should become reference architectures?\n\n - What should we productize versus deliver as managed work?\n\n - Where is the strongest wedge for enterprise customers?\n\n - Which signals show that a customer is ready for managed post-training?\n\n - How do we turn Applied Research work into revenue without diluting the research agenda?\n\n\nREVENUE OWNERSHIP\n\nYou will own high-value customer opportunities from first serious conversation through qualification, scoping, proposal, POC, procurement, and expansion.\n\nYou will not be measured on activity. You will be measured on whether the most important customers move.\n\nThis includes:\n\n - Running discovery with technical and executive stakeholders\n\n - Building the business case and technical wedge\n\n - Owning account strategy with leadership\n\n - Drafting proposals, scopes, and commercial structures\n\n - Coordinating internal workstreams across Applied Research, Product, Engineering, Legal, and Finance\n\n - Creating momentum through ambiguity\n\n - Turning early deployments into expansion and long-term platform revenue\n\n\nAPPLIED RESEARCH PARTNERSHIP\n\nYou will work extremely closely with Applied Research.\n\nThe best version of this role has enough technical taste to understand where an RL/post-training workflow is real, where a customer is hand-waving, and where a sharp Applied Research prototype could unlock a major deal.\n\nYou will help Applied Research prioritize customer-facing work by bringing signal from the field:\n\n - Which evals matter?\n\n - Which environments should we build?\n\n - Which agents or workflows are most commercially valuable?\n\n - Which technical demos will change the customer’s mind?\n\n - Which customer problems are actually research problems in disguise?\n\n\nCATEGORY CREATION\n\nThe market understands compute. It does not yet fully understand full-stack post-training infrastructure.\n\nYou will help write the playbook.\n\nYou will contribute to positioning, sales narratives, customer decks, case studies, reference architectures, launch moments, and internal strategy. You should be able to turn raw customer conversations into crisp language the entire company can use.\n\n\n\nWHAT WE’RE LOOKING FOR\n\nWe are looking for exceptional generalists with rare taste across AI, product, customers, and commercial strategy.\n\nYou might come from:\n\n - Technical GTM at a frontier AI, infra, devtools, or enterprise software company\n\n - Founder or early operator experience at an AI startup\n\n - Product or strategy at a highly technical company\n\n - Forward-deployed engineering, solutions, or applied AI work\n\n - Investing, venture, or strategic finance with deep AI infrastructure exposure\n\n - Research-adjacent roles where you worked directly with customers or product teams\n\nYou should have:\n\n - Strong product and commercial judgment\n\n - Ability to understand technical products quickly\n\n - Excellent written communication\n\n - High agency and comfort with ambiguity\n\n - Taste for what makes a customer problem real\n\n - Ability to work with researchers, engineers, executives, and operators\n\n - Sharp instincts around enterprise buying, POCs, procurement, and expansion\n\n - Obsession with AI, post-training, agents, evals, and infrastructure\n\n - Ability to create structure where none exists\n\nYou do not need to be a researcher, but you should be technical enough to earn trust with researchers and customers.\n\nYou do not need to be a traditional salesperson, but you should be commercially intense enough to close.\n\nYou do not need to be a PM, but you should have strong product taste.\n\n\n\nBONUS POINTS\n\n - Experience with RL, SFT, evals, agent frameworks, or LLM post-training\n\n - Experience selling or deploying infrastructure, AI platforms, devtools, or enterprise AI products\n\n - Experience working with frontier AI labs, model companies, or infra-heavy startups\n\n - Ability to write excellent customer-facing decks, memos, proposals, and launch narratives\n\n - Strong network across AI startups, research labs, or enterprise AI teams\n\n - Founder mentality and willingness to do unglamorous work to win\n\n\n\nWHY THIS ROLE\n\nMost GTM roles ask you to sell a product someone else already defined.\n\nThis role asks you to help define the product, the market, the motion, and the revenue engine at the same time.\n\nYou will work on the hardest commercial and product questions at one of the fastest-growing companies in AI infrastructure. You will sit close to customers building real AI systems, researchers pushing the frontier of post-training, and leadership making company-defining decisions.\n\nIf you want a clean playbook, this is not the role.\n\nIf you want to help invent the playbook for how frontier AI infrastructure gets built, packaged, sold, deployed, and scaled, this is the role.\n\n\n\nWHAT WE OFFER\n\n - Competitive cash compensation and meaningful equity\n\n - Flexible work in San Francisco or hybrid-remote\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conference attendance\n\n - A front-row seat to building the infrastructure layer for open AI\n\n\n\nREADY TO BUILD THE COMMERCIAL ENGINE FOR OPEN SUPERINTELLIGENCE?\n\nApply to help Prime Intellect turn frontier post-training infrastructure into the product, platform, and customer motion that powers the next generation of AI systems."},{"id":"a259487d-9599-42e6-ad42-b97a9772f48b","title":"Forward Deployed AI Strategy Lead","department":"Growth","team":"Growth","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-08T18:32:58.306+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/a259487d-9599-42e6-ad42-b97a9772f48b","applyUrl":"https://jobs.ashbyhq.com/primeintellect/a259487d-9599-42e6-ad42-b97a9772f48b/application","descriptionHtml":"<h1>Forward Deployed AI Strategy Lead</h1><h2><br /><strong>Own Your Intelligence</strong></h2><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2><br />The Role</h2><p style=\"min-height:1.5em\">The most important AI products of the next decade will not be built by simply renting GPUs or calling an API.</p><p style=\"min-height:1.5em\">They will be built by teams that can define the right tasks, construct the right environments, measure the right outcomes, run the right post-training loops, and deploy models that improve on real workflows.</p><p style=\"min-height:1.5em\">Prime Intellect gives customers that capability. Your job is to make it real.</p><p style=\"min-height:1.5em\">As a Forward Deployed AI Strategy Lead, you will work directly with strategic customers to identify high-value AI workflows, translate them into evals and post-training opportunities, scope technical deployments with Applied Research, and turn early experiments into long-term revenue.</p><p style=\"min-height:1.5em\">You are part customer owner, part product strategist, part AI systems thinker, and part commercial operator.</p><p style=\"min-height:1.5em\">You will not sit between the customer and the technical team as a messenger. You will sit with both sides and help invent the answer.</p><h2><br />What You’ll Do</h2><h3>Own Strategic Customer Deployments</h3><p style=\"min-height:1.5em\">You will lead high-priority customer workstreams from first technical discovery through POC, deployment, expansion, and case study.</p><p style=\"min-height:1.5em\">You will work with customers who are trying to build agents, automate complex workflows, improve model performance, reduce inference cost, build domain-specific evals, or run frontier-scale post-training.</p><p style=\"min-height:1.5em\">You will help them answer:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">What should we train or evaluate?</p></li><li><p style=\"min-height:1.5em\">What does success actually mean?</p></li><li><p style=\"min-height:1.5em\">What workflows are worth turning into environments?</p></li><li><p style=\"min-height:1.5em\">What data or traces are needed?</p></li><li><p style=\"min-height:1.5em\">What should be automated, supervised, or measured?</p></li><li><p style=\"min-height:1.5em\">Which model should be adapted?</p></li><li><p style=\"min-height:1.5em\">What is the path from prototype to production?</p></li></ul><h3>Turn Ambiguity Into Scope</h3><p style=\"min-height:1.5em\">Customers rarely arrive with a perfectly defined problem.</p><p style=\"min-height:1.5em\">You will take messy conversations, scattered artifacts, internal docs, product goals, and technical constraints, and turn them into crisp scopes that Applied Research and Engineering can actually execute.</p><p style=\"min-height:1.5em\">You will define:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Use cases</p></li><li><p style=\"min-height:1.5em\">Success metrics</p></li><li><p style=\"min-height:1.5em\">Eval design</p></li><li><p style=\"min-height:1.5em\">Environment requirements</p></li><li><p style=\"min-height:1.5em\">Integration needs</p></li><li><p style=\"min-height:1.5em\">Milestones</p></li><li><p style=\"min-height:1.5em\">Commercial structure</p></li><li><p style=\"min-height:1.5em\">Risks and dependencies</p></li><li><p style=\"min-height:1.5em\">Expansion path</p></li></ul><h3>Partner Deeply With Applied Research</h3><p style=\"min-height:1.5em\">This role works hand-in-hand with Applied Research.</p><p style=\"min-height:1.5em\">You will bring customer signal into the research and product roadmap, helping the team identify which evals, environments, agents, and post-training recipes matter most in the field.</p><p style=\"min-height:1.5em\">You will help prioritize work that can both advance the frontier and unlock meaningful customer outcomes.</p><p style=\"min-height:1.5em\">You should be excited to spend time around questions like:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">How do we convert real-world workflows into reliable RL environments?</p></li><li><p style=\"min-height:1.5em\">What makes an eval useful instead of decorative?</p></li><li><p style=\"min-height:1.5em\">When is a verifier good enough?</p></li><li><p style=\"min-height:1.5em\">What makes a task trainable?</p></li><li><p style=\"min-height:1.5em\">Where does managed RL outperform prompting or manual workflow design?</p></li><li><p style=\"min-height:1.5em\">How do we prove performance improvement to a skeptical customer?</p></li></ul><h3>Build the Repeatable Motion</h3><p style=\"min-height:1.5em\">Every strategic deployment should make the next one easier.</p><p style=\"min-height:1.5em\">You will help build the operating system for Prime Intellect’s applied AI motion:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Discovery templates</p></li><li><p style=\"min-height:1.5em\">Customer qualification frameworks</p></li><li><p style=\"min-height:1.5em\">POC structures</p></li><li><p style=\"min-height:1.5em\">Proposal language</p></li><li><p style=\"min-height:1.5em\">Pricing and packaging inputs</p></li><li><p style=\"min-height:1.5em\">Reference architectures</p></li><li><p style=\"min-height:1.5em\">Case studies</p></li><li><p style=\"min-height:1.5em\">Technical narratives</p></li><li><p style=\"min-height:1.5em\">Deployment playbooks</p></li></ul><p style=\"min-height:1.5em\">You will help turn one-off customer wins into a repeatable category.</p><h3>Drive Revenue</h3><p style=\"min-height:1.5em\">This is a customer-facing role with real revenue responsibility.</p><p style=\"min-height:1.5em\">You will work with leadership to move customers through qualification, legal, scoping, proposal, procurement, POC, deployment, and expansion.</p><p style=\"min-height:1.5em\">You should be comfortable owning senior customer relationships, creating urgency, writing crisp follow-ups, navigating internal and external stakeholders, and making sure important deals do not die in ambiguity.</p><h2><br />What We’re Looking For</h2><p style=\"min-height:1.5em\">We are looking for people who are unusually strong across technical understanding, customer empathy, product judgment, and execution.</p><p style=\"min-height:1.5em\">You might be a strong fit if you have experience in:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Forward deployed engineering or technical GTM</p></li><li><p style=\"min-height:1.5em\">AI product strategy or applied AI</p></li><li><p style=\"min-height:1.5em\">Solutions architecture for highly technical products</p></li><li><p style=\"min-height:1.5em\">Early-stage startup operating roles</p></li><li><p style=\"min-height:1.5em\">Product management for AI, infra, devtools, or enterprise software</p></li><li><p style=\"min-height:1.5em\">ML engineering, applied research, or AI engineering with customer exposure</p></li><li><p style=\"min-height:1.5em\">Venture/investing roles with deep technical and commercial work in AI</p></li></ul><p style=\"min-height:1.5em\">You should have:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong intuition for AI products and workflows</p></li><li><p style=\"min-height:1.5em\">Ability to understand technical systems without needing every detail pre-digested</p></li><li><p style=\"min-height:1.5em\">Excellent written and verbal communication</p></li><li><p style=\"min-height:1.5em\">Comfort operating with executives, researchers, engineers, and operators</p></li><li><p style=\"min-height:1.5em\">High agency and low ego</p></li><li><p style=\"min-height:1.5em\">Ability to run multiple complex customer workstreams</p></li><li><p style=\"min-height:1.5em\">Taste for what makes a deployment valuable</p></li><li><p style=\"min-height:1.5em\">Strong commercial instincts</p></li><li><p style=\"min-height:1.5em\">Deep curiosity about post-training, agents, evals, RL, and AI infrastructure</p></li><li><p style=\"min-height:1.5em\">Ability to make progress before the playbook exists</p></li></ul><h2><br />Bonus Points</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with RL, SFT, evals, agents, MCP, LangGraph, DSPy, Stagehand, Browserbase, or tool-use workflows</p></li><li><p style=\"min-height:1.5em\">Experience working with enterprise AI teams or frontier AI companies</p></li><li><p style=\"min-height:1.5em\">Ability to read traces, product docs, API docs, or technical specs and turn them into a deployment plan</p></li><li><p style=\"min-height:1.5em\">Experience writing proposals, customer memos, technical scopes, or launch narratives</p></li><li><p style=\"min-height:1.5em\">Founder or early startup experience</p></li><li><p style=\"min-height:1.5em\">Strong network across AI startups, research labs, or enterprise software buyers</p></li></ul><h2><br />Why This Role</h2><p style=\"min-height:1.5em\">This is one of the highest-leverage roles at Prime Intellect.</p><p style=\"min-height:1.5em\">The frontier is moving from models to systems: agents, environments, evals, training loops, and deployment infrastructure. Most companies know they need to adapt models to their own workflows, but they do not know how to turn that ambition into a working system.</p><p style=\"min-height:1.5em\">You will be the person who helps them get there.</p><p style=\"min-height:1.5em\">You will work on customer problems that are technically real, commercially urgent, and strategically important. You will help shape the product, close the revenue, and define the emerging category of full-stack post-training infrastructure.</p><p style=\"min-height:1.5em\">This is a role for builders who want to be close to the frontier and close to the market.</p><h2><br />What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Competitive cash compensation and meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work in San Francisco or hybrid-remote</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">Direct exposure to frontier AI labs, leading AI startups, and enterprise AI teams</p></li><li><p style=\"min-height:1.5em\">A rare opportunity to help define how the next generation of AI systems are trained, evaluated, and deployed</p></li></ul><h2><br />Ready to Build the Interface Between Frontier AI and the Real World?</h2><p style=\"min-height:1.5em\">Apply to help Prime Intellect turn ambitious customer workflows into post-training systems, revenue, and the foundation for open superintelligence.</p>","descriptionPlain":"FORWARD DEPLOYED AI STRATEGY LEAD\n\n\n\nOWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. \n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\n\nTHE ROLE\n\nThe most important AI products of the next decade will not be built by simply renting GPUs or calling an API.\n\nThey will be built by teams that can define the right tasks, construct the right environments, measure the right outcomes, run the right post-training loops, and deploy models that improve on real workflows.\n\nPrime Intellect gives customers that capability. Your job is to make it real.\n\nAs a Forward Deployed AI Strategy Lead, you will work directly with strategic customers to identify high-value AI workflows, translate them into evals and post-training opportunities, scope technical deployments with Applied Research, and turn early experiments into long-term revenue.\n\nYou are part customer owner, part product strategist, part AI systems thinker, and part commercial operator.\n\nYou will not sit between the customer and the technical team as a messenger. You will sit with both sides and help invent the answer.\n\n\n\nWHAT YOU’LL DO\n\n\nOWN STRATEGIC CUSTOMER DEPLOYMENTS\n\nYou will lead high-priority customer workstreams from first technical discovery through POC, deployment, expansion, and case study.\n\nYou will work with customers who are trying to build agents, automate complex workflows, improve model performance, reduce inference cost, build domain-specific evals, or run frontier-scale post-training.\n\nYou will help them answer:\n\n - What should we train or evaluate?\n\n - What does success actually mean?\n\n - What workflows are worth turning into environments?\n\n - What data or traces are needed?\n\n - What should be automated, supervised, or measured?\n\n - Which model should be adapted?\n\n - What is the path from prototype to production?\n\n\nTURN AMBIGUITY INTO SCOPE\n\nCustomers rarely arrive with a perfectly defined problem.\n\nYou will take messy conversations, scattered artifacts, internal docs, product goals, and technical constraints, and turn them into crisp scopes that Applied Research and Engineering can actually execute.\n\nYou will define:\n\n - Use cases\n\n - Success metrics\n\n - Eval design\n\n - Environment requirements\n\n - Integration needs\n\n - Milestones\n\n - Commercial structure\n\n - Risks and dependencies\n\n - Expansion path\n\n\nPARTNER DEEPLY WITH APPLIED RESEARCH\n\nThis role works hand-in-hand with Applied Research.\n\nYou will bring customer signal into the research and product roadmap, helping the team identify which evals, environments, agents, and post-training recipes matter most in the field.\n\nYou will help prioritize work that can both advance the frontier and unlock meaningful customer outcomes.\n\nYou should be excited to spend time around questions like:\n\n - How do we convert real-world workflows into reliable RL environments?\n\n - What makes an eval useful instead of decorative?\n\n - When is a verifier good enough?\n\n - What makes a task trainable?\n\n - Where does managed RL outperform prompting or manual workflow design?\n\n - How do we prove performance improvement to a skeptical customer?\n\n\nBUILD THE REPEATABLE MOTION\n\nEvery strategic deployment should make the next one easier.\n\nYou will help build the operating system for Prime Intellect’s applied AI motion:\n\n - Discovery templates\n\n - Customer qualification frameworks\n\n - POC structures\n\n - Proposal language\n\n - Pricing and packaging inputs\n\n - Reference architectures\n\n - Case studies\n\n - Technical narratives\n\n - Deployment playbooks\n\nYou will help turn one-off customer wins into a repeatable category.\n\n\nDRIVE REVENUE\n\nThis is a customer-facing role with real revenue responsibility.\n\nYou will work with leadership to move customers through qualification, legal, scoping, proposal, procurement, POC, deployment, and expansion.\n\nYou should be comfortable owning senior customer relationships, creating urgency, writing crisp follow-ups, navigating internal and external stakeholders, and making sure important deals do not die in ambiguity.\n\n\n\nWHAT WE’RE LOOKING FOR\n\nWe are looking for people who are unusually strong across technical understanding, customer empathy, product judgment, and execution.\n\nYou might be a strong fit if you have experience in:\n\n - Forward deployed engineering or technical GTM\n\n - AI product strategy or applied AI\n\n - Solutions architecture for highly technical products\n\n - Early-stage startup operating roles\n\n - Product management for AI, infra, devtools, or enterprise software\n\n - ML engineering, applied research, or AI engineering with customer exposure\n\n - Venture/investing roles with deep technical and commercial work in AI\n\nYou should have:\n\n - Strong intuition for AI products and workflows\n\n - Ability to understand technical systems without needing every detail pre-digested\n\n - Excellent written and verbal communication\n\n - Comfort operating with executives, researchers, engineers, and operators\n\n - High agency and low ego\n\n - Ability to run multiple complex customer workstreams\n\n - Taste for what makes a deployment valuable\n\n - Strong commercial instincts\n\n - Deep curiosity about post-training, agents, evals, RL, and AI infrastructure\n\n - Ability to make progress before the playbook exists\n\n\n\nBONUS POINTS\n\n - Experience with RL, SFT, evals, agents, MCP, LangGraph, DSPy, Stagehand, Browserbase, or tool-use workflows\n\n - Experience working with enterprise AI teams or frontier AI companies\n\n - Ability to read traces, product docs, API docs, or technical specs and turn them into a deployment plan\n\n - Experience writing proposals, customer memos, technical scopes, or launch narratives\n\n - Founder or early startup experience\n\n - Strong network across AI startups, research labs, or enterprise software buyers\n\n\n\nWHY THIS ROLE\n\nThis is one of the highest-leverage roles at Prime Intellect.\n\nThe frontier is moving from models to systems: agents, environments, evals, training loops, and deployment infrastructure. Most companies know they need to adapt models to their own workflows, but they do not know how to turn that ambition into a working system.\n\nYou will be the person who helps them get there.\n\nYou will work on customer problems that are technically real, commercially urgent, and strategically important. You will help shape the product, close the revenue, and define the emerging category of full-stack post-training infrastructure.\n\nThis is a role for builders who want to be close to the frontier and close to the market.\n\n\n\nWHAT WE OFFER\n\n - Competitive cash compensation and meaningful equity\n\n - Flexible work in San Francisco or hybrid-remote\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conference attendance\n\n - Direct exposure to frontier AI labs, leading AI startups, and enterprise AI teams\n\n - A rare opportunity to help define how the next generation of AI systems are trained, evaluated, and deployed\n\n\n\nREADY TO BUILD THE INTERFACE BETWEEN FRONTIER AI AND THE REAL WORLD?\n\nApply to help Prime Intellect turn ambitious customer workflows into post-training systems, revenue, and the foundation for open superintelligence."},{"id":"cf9f2534-962f-41b2-b240-89f3e85f5b6d","title":"Head of Talent","department":"Finance / Operations","team":"Finance / Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-08-10T18:27:25.122+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/cf9f2534-962f-41b2-b240-89f3e85f5b6d","applyUrl":"https://jobs.ashbyhq.com/primeintellect/cf9f2534-962f-41b2-b240-89f3e85f5b6d/application","descriptionHtml":"<h1>Head of Talent</h1><p style=\"min-height:1.5em\"></p><h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. </p><p style=\"min-height:1.5em\"></p><h2>Role Impact</h2><p style=\"min-height:1.5em\">Talent is the single highest-leverage input at Prime Intellect. Every frontier researcher, systems engineer, and operator we hire compounds directly into what the open ecosystem can build. This role owns that compounding.</p><p style=\"min-height:1.5em\">As Head of Talent, you will own recruiting end-to-end as we scale from ~40 to ~100 people over the next twelve months, weighted heavily toward frontier research and infrastructure engineering — the two most competitive talent markets in tech. You will personally run our most important searches, source candidates who are not on the market, and close them against offers from the largest labs.</p><p style=\"min-height:1.5em\">Beyond individual hires, you will define how Prime Intellect recruits at scale: building the sourcing engine, closing playbooks, interview architecture, and compensation frameworks that let us maintain an exceptionally high bar while moving faster than incumbents. This is a founding recruiting leader role reporting directly to the founders, with full ownership of the function, meaningful equity, and a direct line into every strategic hiring decision.</p><p style=\"min-height:1.5em\"></p><h2>What You'll Do</h2><p style=\"min-height:1.5em\"><strong>Own the Highest-Priority Searches</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Personally run our most important searches across research, infrastructure, and leadership hires</p></li><li><p style=\"min-height:1.5em\">Source candidates directly — through your own network, cold outreach, and targeted campaigns — for roles where inbound alone will never surface the right person</p></li><li><p style=\"min-height:1.5em\">Close candidates against competing offers from frontier labs, hyperscalers, and top AI startups</p></li><li><p style=\"min-height:1.5em\">Serve as a trusted partner to the founders and hiring managers on candidate strategy, leveling, and offer construction</p></li></ul><p style=\"min-height:1.5em\"><strong>Build the Sourcing &amp; Closing Engine</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and run the sourcing motion for frontier research talent (labs, PhD programs, top open-source contributors) and elite systems engineering talent (distributed systems, GPU infrastructure, ML systems)</p></li><li><p style=\"min-height:1.5em\">Build closing playbooks that reflect what actually moves technical candidates: research autonomy, compute access, publication norms, equity, and mission</p></li><li><p style=\"min-height:1.5em\">Stand up the tooling, data, and pipeline visibility we need to run 60+ hires per year without dropping quality</p></li><li><p style=\"min-height:1.5em\">Define and enforce the hiring bar across the company as we scale</p></li></ul><p style=\"min-height:1.5em\"><strong>Systems, Team &amp; Operational Scale</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Hire and lead a small recruiting team over time (sourcers, coordinators, and eventually recruiters), staying deeply hands-on yourself</p></li><li><p style=\"min-height:1.5em\">Build interview architecture — rubrics, calibration, debriefs, decision-making — that produces consistent hiring outcomes as more people participate</p></li><li><p style=\"min-height:1.5em\">Own recruiting operations, candidate experience, and reporting end-to-end</p></li><li><p style=\"min-height:1.5em\">Partner with finance and the founders on compensation philosophy, leveling, and equity strategy as we grow</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">5+ years of technical recruiting experience, with meaningful time at a frontier AI lab, top AI startup, or elite technical company</p></li><li><p style=\"min-height:1.5em\">Direct experience recruiting ML researchers, frontier research talent, or elite systems / distributed engineers — not just \"technical roles\" broadly</p></li><li><p style=\"min-height:1.5em\">Proven ability to source and close candidates who are not actively looking, against competing offers from top labs</p></li><li><p style=\"min-height:1.5em\">Track record of personally owning senior and hard-to-fill searches end-to-end</p></li><li><p style=\"min-height:1.5em\">Comfort operating as a player-coach: running your own searches while building the systems and eventually the team underneath you</p></li><li><p style=\"min-height:1.5em\">Strong judgment on candidate quality and leveling; willingness to hold a high bar under pressure</p></li><li><p style=\"min-height:1.5em\">High ownership, direct communication, and appetite for working closely with founders on the most consequential decisions in the company</p></li><li><p style=\"min-height:1.5em\">Energized by building a recruiting function from the ground up in a fast-moving environment</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Nice-to-Haves</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Prior experience as a founding recruiter, Head of Recruiting, or senior recruiting lead at a fast-growing technical company</p></li><li><p style=\"min-height:1.5em\">Existing network in the frontier AI research or GPU / ML infrastructure community</p></li><li><p style=\"min-height:1.5em\">Experience closing candidates against top AI lab offers</p></li><li><p style=\"min-height:1.5em\">Familiarity with open-source ecosystems and the researchers and engineers who lead them</p></li><li><p style=\"min-height:1.5em\">Background scaling recruiting operations, tooling, and interview systems at a rapidly growing company</p></li></ul><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">$250-300k+ cash compensation + meaningful equity</p></li><li><p style=\"min-height:1.5em\">Flexible work environment</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conference attendance</p></li></ul>","descriptionPlain":"HEAD OF TALENT\n\n\n\n\nOWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. \n\n\n\n\nROLE IMPACT\n\nTalent is the single highest-leverage input at Prime Intellect. Every frontier researcher, systems engineer, and operator we hire compounds directly into what the open ecosystem can build. This role owns that compounding.\n\nAs Head of Talent, you will own recruiting end-to-end as we scale from ~40 to ~100 people over the next twelve months, weighted heavily toward frontier research and infrastructure engineering — the two most competitive talent markets in tech. You will personally run our most important searches, source candidates who are not on the market, and close them against offers from the largest labs.\n\nBeyond individual hires, you will define how Prime Intellect recruits at scale: building the sourcing engine, closing playbooks, interview architecture, and compensation frameworks that let us maintain an exceptionally high bar while moving faster than incumbents. This is a founding recruiting leader role reporting directly to the founders, with full ownership of the function, meaningful equity, and a direct line into every strategic hiring decision.\n\n\n\n\nWHAT YOU'LL DO\n\nOwn the Highest-Priority Searches\n\n - Personally run our most important searches across research, infrastructure, and leadership hires\n\n - Source candidates directly — through your own network, cold outreach, and targeted campaigns — for roles where inbound alone will never surface the right person\n\n - Close candidates against competing offers from frontier labs, hyperscalers, and top AI startups\n\n - Serve as a trusted partner to the founders and hiring managers on candidate strategy, leveling, and offer construction\n\nBuild the Sourcing & Closing Engine\n\n - Design and run the sourcing motion for frontier research talent (labs, PhD programs, top open-source contributors) and elite systems engineering talent (distributed systems, GPU infrastructure, ML systems)\n\n - Build closing playbooks that reflect what actually moves technical candidates: research autonomy, compute access, publication norms, equity, and mission\n\n - Stand up the tooling, data, and pipeline visibility we need to run 60+ hires per year without dropping quality\n\n - Define and enforce the hiring bar across the company as we scale\n\nSystems, Team & Operational Scale\n\n - Hire and lead a small recruiting team over time (sourcers, coordinators, and eventually recruiters), staying deeply hands-on yourself\n\n - Build interview architecture — rubrics, calibration, debriefs, decision-making — that produces consistent hiring outcomes as more people participate\n\n - Own recruiting operations, candidate experience, and reporting end-to-end\n\n - Partner with finance and the founders on compensation philosophy, leveling, and equity strategy as we grow\n\n\n\n\nREQUIREMENTS\n\n - 5+ years of technical recruiting experience, with meaningful time at a frontier AI lab, top AI startup, or elite technical company\n\n - Direct experience recruiting ML researchers, frontier research talent, or elite systems / distributed engineers — not just \"technical roles\" broadly\n\n - Proven ability to source and close candidates who are not actively looking, against competing offers from top labs\n\n - Track record of personally owning senior and hard-to-fill searches end-to-end\n\n - Comfort operating as a player-coach: running your own searches while building the systems and eventually the team underneath you\n\n - Strong judgment on candidate quality and leveling; willingness to hold a high bar under pressure\n\n - High ownership, direct communication, and appetite for working closely with founders on the most consequential decisions in the company\n\n - Energized by building a recruiting function from the ground up in a fast-moving environment\n\n\n\n\nNICE-TO-HAVES\n\n - Prior experience as a founding recruiter, Head of Recruiting, or senior recruiting lead at a fast-growing technical company\n\n - Existing network in the frontier AI research or GPU / ML infrastructure community\n\n - Experience closing candidates against top AI lab offers\n\n - Familiarity with open-source ecosystems and the researchers and engineers who lead them\n\n - Background scaling recruiting operations, tooling, and interview systems at a rapidly growing company\n\n\n\n\nWHAT WE OFFER\n\n - $250-300k+ cash compensation + meaningful equity\n\n - Flexible work environment\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conference attendance"},{"id":"8597d151-46db-4c67-a809-5d40daae7185","title":"Member of Technical Staff - Prime Agent","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-09-17T22:44:23.257+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/8597d151-46db-4c67-a809-5d40daae7185","applyUrl":"https://jobs.ashbyhq.com/primeintellect/8597d151-46db-4c67-a809-5d40daae7185/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll help build Prime Agent, our open-source coding and research agent. This is a generalist software engineering role spanning product development and the underlying agent systems. You'll own features end-to-end, from design through deployment and monitoring, and ship at the pace of an early-stage company tackling one of the most important problems in AI.</p><p style=\"min-height:1.5em\">This role is based in our San Francisco office. Candidates must be based in San Francisco and work in person. This is not a remote role and is not open in other locations.</p><h2>Core Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build intuitive interfaces for working with agents and managing their tasks</p></li><li><p style=\"min-height:1.5em\">Own features end-to-end, from design through deployment and operation</p></li><li><p style=\"min-height:1.5em\">Work with users to understand their needs and turn feedback into product improvements</p></li><li><p style=\"min-height:1.5em\">Work closely with teams across the Prime ecosystem to build cloud agents, self-improving loops, and integrations for traces and post-training</p></li><li><p style=\"min-height:1.5em\">Work closely with researchers to turn new agent capabilities into reliable product features</p></li><li><p style=\"min-height:1.5em\">Contribute to internal tooling, automation, and developer experience improvements</p></li></ul><h2>Technical Requirements</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Strong software engineering skills in TypeScript and Python</p></li><li><p style=\"min-height:1.5em\">Experience building developer tools, dashboards, platform products, and working with agent harnesses</p></li><li><p style=\"min-height:1.5em\">Strong product judgment and attention to user experience, with the ability to turn complex capabilities into intuitive workflows</p></li><li><p style=\"min-height:1.5em\">Experience building reliable systems with asynchronous execution and real-time interactions</p></li><li><p style=\"min-height:1.5em\">Awareness of what's happening at the frontier - new models, agent capabilities, and tooling - and the ability to translate that into product decisions</p></li><li><p style=\"min-height:1.5em\">A bias toward shipping, ownership of production code, and pragmatic engineering judgment</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience building coding agents, agent harnesses, or developer tools powered by LLMs</p></li><li><p style=\"min-height:1.5em\">CLI or terminal UI development</p></li><li><p style=\"min-height:1.5em\">WebSocket / real-time systems experience</p></li><li><p style=\"min-height:1.5em\">Open-source contributions</p></li><li><p style=\"min-height:1.5em\">Prior experience at an early-stage startup</p></li></ul><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation range of $150,000–$300,000 with significant equity incentives</p></li><li><p style=\"min-height:1.5em\">In-person collaboration with the Prime Agent team in our San Francisco office</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li><li><p style=\"min-height:1.5em\">Opportunity to shape the future of open AI development</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.</p><p style=\"min-height:1.5em\">We value potential over perfection - if you're a strong generalist engineer who is passionate about democratizing AI development, we want to talk to you.</p><p style=\"min-height:1.5em\">Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nROLE IMPACT\n\nYou'll help build Prime Agent, our open-source coding and research agent. This is a generalist software engineering role spanning product development and the underlying agent systems. You'll own features end-to-end, from design through deployment and monitoring, and ship at the pace of an early-stage company tackling one of the most important problems in AI.\n\nThis role is based in our San Francisco office. Candidates must be based in San Francisco and work in person. This is not a remote role and is not open in other locations.\n\n\nCORE RESPONSIBILITIES\n\n - Build intuitive interfaces for working with agents and managing their tasks\n\n - Own features end-to-end, from design through deployment and operation\n\n - Work with users to understand their needs and turn feedback into product improvements\n\n - Work closely with teams across the Prime ecosystem to build cloud agents, self-improving loops, and integrations for traces and post-training\n\n - Work closely with researchers to turn new agent capabilities into reliable product features\n\n - Contribute to internal tooling, automation, and developer experience improvements\n\n\nTECHNICAL REQUIREMENTS\n\n - Strong software engineering skills in TypeScript and Python\n\n - Experience building developer tools, dashboards, platform products, and working with agent harnesses\n\n - Strong product judgment and attention to user experience, with the ability to turn complex capabilities into intuitive workflows\n\n - Experience building reliable systems with asynchronous execution and real-time interactions\n\n - Awareness of what's happening at the frontier - new models, agent capabilities, and tooling - and the ability to translate that into product decisions\n\n - A bias toward shipping, ownership of production code, and pragmatic engineering judgment\n\n\nNICE TO HAVE\n\n - Experience building coding agents, agent harnesses, or developer tools powered by LLMs\n\n - CLI or terminal UI development\n\n - WebSocket / real-time systems experience\n\n - Open-source contributions\n\n - Prior experience at an early-stage startup\n\n\nWHAT WE OFFER\n\n - Cash compensation range of $150,000–$300,000 with significant equity incentives\n\n - In-person collaboration with the Prime Agent team in our San Francisco office\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n - Opportunity to shape the future of open AI development\n\n\nGROWTH OPPORTUNITY\n\nYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.\n\nWe value potential over perfection - if you're a strong generalist engineer who is passionate about democratizing AI development, we want to talk to you.\n\nReady to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone."},{"id":"1b1a39a8-bd5d-423a-b45d-816dd64dfb2d","title":"Member of Technical Staff - Bare Metal & Fleet Provisioning","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-09-17T22:46:01.667+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/1b1a39a8-bd5d-423a-b45d-816dd64dfb2d","applyUrl":"https://jobs.ashbyhq.com/primeintellect/1b1a39a8-bd5d-423a-b45d-816dd64dfb2d/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll build the systems that turn bare-metal GPU servers into reliable, production-ready compute. Own the machine lifecycle from discovery and provisioning through validation, upgrades, repair, and secure reuse, reducing manual work as our fleet grows.</p><h2>Core Technical Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build automated discovery, network boot, OS imaging, and configuration workflows for GPU servers</p></li><li><p style=\"min-height:1.5em\">Automate BIOS, BMC, NIC, GPU driver, and firmware configuration with staged rollouts and safe recovery paths</p></li><li><p style=\"min-height:1.5em\">Develop hardware inventory and lifecycle services that track machine identity, configuration, health, and readiness</p></li><li><p style=\"min-height:1.5em\">Create acceptance tests and burn-in workflows for GPUs, memory, storage, and interconnects before capacity enters production</p></li><li><p style=\"min-height:1.5em\">Integrate provisioning and health checks with SLURM, Kubernetes, and compute allocation systems</p></li><li><p style=\"min-height:1.5em\">Build observability, quarantine, repair, and re-provisioning workflows; partner with datacenter teams to resolve hardware failures</p></li><li><p style=\"min-height:1.5em\">Implement secure credential handling, tenant isolation, and data sanitization across the server lifecycle</p></li></ul><h2>Technical Requirements</h2><h3>Required Experience</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3+ years of experience operating Linux servers or building bare-metal infrastructure automation in production</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with PXE/iPXE, DHCP, image provisioning, and out-of-band management such as Redfish or IPMI</p></li><li><p style=\"min-height:1.5em\">Strong software engineering and debugging skills in Python, Go, or a comparable language, plus Bash</p></li><li><p style=\"min-height:1.5em\">Experience designing reliable automation that handles partial failures, retries, and configuration drift</p></li><li><p style=\"min-height:1.5em\">Ability to own operational incidents and collaborate across hardware, networking, and platform teams</p></li></ul><h3>Infrastructure Skills</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Linux boot, systemd, kernel and driver troubleshooting, and OS image management</p></li><li><p style=\"min-height:1.5em\">Infrastructure automation with tools such as Ansible and Terraform</p></li><li><p style=\"min-height:1.5em\">GPU server diagnostics, PCIe topology, BMC telemetry, and firmware compatibility</p></li><li><p style=\"min-height:1.5em\">Network fundamentals including addressing, VLANs, DNS, and management networks</p></li><li><p style=\"min-height:1.5em\">Metrics, logs, alerting, and auditable configuration management</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with large NVIDIA GPU fleets, DGX/HGX platforms, or heterogeneous server vendors</p></li><li><p style=\"min-height:1.5em\">Experience with MAAS, Ironic, Tinkerbell, or similar provisioning systems</p></li><li><p style=\"min-height:1.5em\">Kubernetes or SLURM node lifecycle integrations</p></li><li><p style=\"min-height:1.5em\">Hardware qualification, automated burn-in, and fleet health scoring</p></li><li><p style=\"min-height:1.5em\">Contributions to open-source infrastructure tooling</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.</p><p style=\"min-height:1.5em\">We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and join us in our mission to democratize access to planetary scale computing.</p><h2>Compensation</h2><p style=\"min-height:1.5em\">Cash compensation range of $150,000–$300,000 plus equity incentives.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nROLE IMPACT\n\nYou'll build the systems that turn bare-metal GPU servers into reliable, production-ready compute. Own the machine lifecycle from discovery and provisioning through validation, upgrades, repair, and secure reuse, reducing manual work as our fleet grows.\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n - Build automated discovery, network boot, OS imaging, and configuration workflows for GPU servers\n\n - Automate BIOS, BMC, NIC, GPU driver, and firmware configuration with staged rollouts and safe recovery paths\n\n - Develop hardware inventory and lifecycle services that track machine identity, configuration, health, and readiness\n\n - Create acceptance tests and burn-in workflows for GPUs, memory, storage, and interconnects before capacity enters production\n\n - Integrate provisioning and health checks with SLURM, Kubernetes, and compute allocation systems\n\n - Build observability, quarantine, repair, and re-provisioning workflows; partner with datacenter teams to resolve hardware failures\n\n - Implement secure credential handling, tenant isolation, and data sanitization across the server lifecycle\n\n\nTECHNICAL REQUIREMENTS\n\n\nREQUIRED EXPERIENCE\n\n - 3+ years of experience operating Linux servers or building bare-metal infrastructure automation in production\n\n - Hands-on experience with PXE/iPXE, DHCP, image provisioning, and out-of-band management such as Redfish or IPMI\n\n - Strong software engineering and debugging skills in Python, Go, or a comparable language, plus Bash\n\n - Experience designing reliable automation that handles partial failures, retries, and configuration drift\n\n - Ability to own operational incidents and collaborate across hardware, networking, and platform teams\n\n\nINFRASTRUCTURE SKILLS\n\n - Linux boot, systemd, kernel and driver troubleshooting, and OS image management\n\n - Infrastructure automation with tools such as Ansible and Terraform\n\n - GPU server diagnostics, PCIe topology, BMC telemetry, and firmware compatibility\n\n - Network fundamentals including addressing, VLANs, DNS, and management networks\n\n - Metrics, logs, alerting, and auditable configuration management\n\n\nNICE TO HAVE\n\n - Experience with large NVIDIA GPU fleets, DGX/HGX platforms, or heterogeneous server vendors\n\n - Experience with MAAS, Ironic, Tinkerbell, or similar provisioning systems\n\n - Kubernetes or SLURM node lifecycle integrations\n\n - Hardware qualification, automated burn-in, and fleet health scoring\n\n - Contributions to open-source infrastructure tooling\n\n\nGROWTH OPPORTUNITY\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\n\nCOMPENSATION\n\nCash compensation range of $150,000–$300,000 plus equity incentives."},{"id":"a33eb95d-3a3f-40b6-98c5-cfc436d4aa44","title":"Member of Technical Staff - Datacenter Networking","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-09-17T22:46:39.786+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/a33eb95d-3a3f-40b6-98c5-cfc436d4aa44","applyUrl":"https://jobs.ashbyhq.com/primeintellect/a33eb95d-3a3f-40b6-98c5-cfc436d4aa44/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll design and operate the networks that connect large GPU clusters. Own the reliability and performance of training fabrics, storage networks, and management connectivity so distributed workloads can scale without the network becoming the bottleneck.</p><h2>Core Technical Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and deploy scalable datacenter network topologies for GPU training, inference, storage, and management traffic</p></li><li><p style=\"min-height:1.5em\">Configure and operate high-performance Ethernet/RoCE and InfiniBand fabrics with clear standards for routing, redundancy, and capacity</p></li><li><p style=\"min-height:1.5em\">Automate network provisioning, configuration validation, upgrades, and rollback procedures</p></li><li><p style=\"min-height:1.5em\">Diagnose packet loss, congestion, link failures, and collective communication performance across hosts and switches</p></li><li><p style=\"min-height:1.5em\">Benchmark end-to-end network performance with infrastructure and ML teams, translating workload needs into measurable acceptance criteria</p></li><li><p style=\"min-height:1.5em\">Build monitoring for port health, errors, utilization, congestion, and fabric topology; improve incident response and runbooks</p></li><li><p style=\"min-height:1.5em\">Partner with datacenter operators and hardware vendors on cabling, optics, deployment readiness, and failure resolution</p></li></ul><h2>Technical Requirements</h2><h3>Required Experience</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3+ years of production datacenter networking experience</p></li><li><p style=\"min-height:1.5em\">Strong understanding of Ethernet, TCP/IP, routing, switching, and redundant network design</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with high-performance GPU networking using InfiniBand or RoCE</p></li><li><p style=\"min-height:1.5em\">Experience troubleshooting network problems across Linux hosts, NICs, switches, and physical links</p></li><li><p style=\"min-height:1.5em\">Ability to automate network operations with Python, Ansible, or comparable tools</p></li></ul><h3>Infrastructure Skills</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Leaf-spine architectures, BGP, ECMP, VLANs, and network segmentation</p></li><li><p style=\"min-height:1.5em\">RDMA concepts and performance tuning; congestion control and lossless Ethernet considerations</p></li><li><p style=\"min-height:1.5em\">Linux networking, NIC drivers and firmware, packet capture, and throughput/latency testing</p></li><li><p style=\"min-height:1.5em\">Optics, transceivers, cable management, and link-level diagnostics</p></li><li><p style=\"min-height:1.5em\">Safe change management, configuration versioning, telemetry, and alerting</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience operating 400G/800G networks or large multi-rack GPU clusters</p></li><li><p style=\"min-height:1.5em\">NVIDIA Spectrum or Quantum networking experience</p></li><li><p style=\"min-height:1.5em\">NCCL performance analysis and distributed training troubleshooting</p></li><li><p style=\"min-height:1.5em\">EVPN/VXLAN, SONiC, or network source-of-truth systems</p></li><li><p style=\"min-height:1.5em\">Experience with network simulation, automated validation, and capacity planning</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.</p><p style=\"min-height:1.5em\">We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and join us in our mission to democratize access to planetary scale computing.</p><h2>Compensation</h2><p style=\"min-height:1.5em\">Cash compensation range of $150,000–$300,000 plus equity incentives.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nROLE IMPACT\n\nYou'll design and operate the networks that connect large GPU clusters. Own the reliability and performance of training fabrics, storage networks, and management connectivity so distributed workloads can scale without the network becoming the bottleneck.\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n - Design and deploy scalable datacenter network topologies for GPU training, inference, storage, and management traffic\n\n - Configure and operate high-performance Ethernet/RoCE and InfiniBand fabrics with clear standards for routing, redundancy, and capacity\n\n - Automate network provisioning, configuration validation, upgrades, and rollback procedures\n\n - Diagnose packet loss, congestion, link failures, and collective communication performance across hosts and switches\n\n - Benchmark end-to-end network performance with infrastructure and ML teams, translating workload needs into measurable acceptance criteria\n\n - Build monitoring for port health, errors, utilization, congestion, and fabric topology; improve incident response and runbooks\n\n - Partner with datacenter operators and hardware vendors on cabling, optics, deployment readiness, and failure resolution\n\n\nTECHNICAL REQUIREMENTS\n\n\nREQUIRED EXPERIENCE\n\n - 3+ years of production datacenter networking experience\n\n - Strong understanding of Ethernet, TCP/IP, routing, switching, and redundant network design\n\n - Hands-on experience with high-performance GPU networking using InfiniBand or RoCE\n\n - Experience troubleshooting network problems across Linux hosts, NICs, switches, and physical links\n\n - Ability to automate network operations with Python, Ansible, or comparable tools\n\n\nINFRASTRUCTURE SKILLS\n\n - Leaf-spine architectures, BGP, ECMP, VLANs, and network segmentation\n\n - RDMA concepts and performance tuning; congestion control and lossless Ethernet considerations\n\n - Linux networking, NIC drivers and firmware, packet capture, and throughput/latency testing\n\n - Optics, transceivers, cable management, and link-level diagnostics\n\n - Safe change management, configuration versioning, telemetry, and alerting\n\n\nNICE TO HAVE\n\n - Experience operating 400G/800G networks or large multi-rack GPU clusters\n\n - NVIDIA Spectrum or Quantum networking experience\n\n - NCCL performance analysis and distributed training troubleshooting\n\n - EVPN/VXLAN, SONiC, or network source-of-truth systems\n\n - Experience with network simulation, automated validation, and capacity planning\n\n\nGROWTH OPPORTUNITY\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\n\nCOMPENSATION\n\nCash compensation range of $150,000–$300,000 plus equity incentives."},{"id":"074f0761-2e12-44ad-963f-beb1aca73e8a","title":"Member of Technical Staff - Storage Infrastructure","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-09-17T22:47:15.499+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/074f0761-2e12-44ad-963f-beb1aca73e8a","applyUrl":"https://jobs.ashbyhq.com/primeintellect/074f0761-2e12-44ad-963f-beb1aca73e8a/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll build and operate the storage systems that feed frontier AI workloads. Own reliable, high-throughput access to datasets, checkpoints, and model artifacts, balancing performance, durability, availability, and cost as GPU clusters scale.</p><h2>Core Technical Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design and operate storage architectures for training datasets, checkpointing, inference artifacts, and shared research workflows</p></li><li><p style=\"min-height:1.5em\">Deploy and tune parallel filesystems, object storage, and local NVMe caching for demanding AI workloads</p></li><li><p style=\"min-height:1.5em\">Benchmark throughput, latency, metadata performance, and concurrent access with representative training and checkpoint workloads</p></li><li><p style=\"min-height:1.5em\">Build provisioning, capacity planning, lifecycle management, and operational automation for storage services</p></li><li><p style=\"min-height:1.5em\">Design and test replication, recovery, backup, and failure-handling procedures with explicit durability and availability targets</p></li><li><p style=\"min-height:1.5em\">Diagnose performance and reliability issues across applications, clients, networks, filesystems, and devices</p></li><li><p style=\"min-height:1.5em\">Implement access controls, tenant separation, quotas, monitoring, and runbooks; collaborate with compute and networking teams</p></li></ul><h2>Technical Requirements</h2><h3>Required Experience</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3+ years building or operating production distributed storage systems</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with at least one parallel or distributed filesystem or object storage platform, such as Lustre, BeeGFS, Ceph, or GPFS</p></li><li><p style=\"min-height:1.5em\">Strong Linux administration and performance troubleshooting skills</p></li><li><p style=\"min-height:1.5em\">Experience automating infrastructure operations in Python, Go, Bash, or similar languages</p></li><li><p style=\"min-height:1.5em\">Understanding of storage failure modes, data integrity, consistency, replication, and recovery</p></li></ul><h3>Infrastructure Skills</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Block, file, and object storage semantics and their performance tradeoffs</p></li><li><p style=\"min-height:1.5em\">NVMe/SSD performance, filesystem tuning, I/O profiling, and benchmarking</p></li><li><p style=\"min-height:1.5em\">High-throughput storage networking and distributed client behavior</p></li><li><p style=\"min-height:1.5em\">Capacity forecasting, observability, alerting, and safe maintenance procedures</p></li><li><p style=\"min-height:1.5em\">Authentication, authorization, encryption, and secure data lifecycle management</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience supporting large GPU training clusters and high-volume checkpoint workloads</p></li><li><p style=\"min-height:1.5em\">S3-compatible object storage, data tiering, or distributed caching</p></li><li><p style=\"min-height:1.5em\">RDMA-enabled storage or GPUDirect Storage experience</p></li><li><p style=\"min-height:1.5em\">Kubernetes storage integrations or SLURM environments</p></li><li><p style=\"min-height:1.5em\">Storage cost optimization and contributions to open-source storage systems</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.</p><p style=\"min-height:1.5em\">We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and join us in our mission to democratize access to planetary scale computing.</p><h2>Compensation</h2><p style=\"min-height:1.5em\">Cash compensation range of $150,000–$300,000 plus equity incentives.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nROLE IMPACT\n\nYou'll build and operate the storage systems that feed frontier AI workloads. Own reliable, high-throughput access to datasets, checkpoints, and model artifacts, balancing performance, durability, availability, and cost as GPU clusters scale.\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n - Design and operate storage architectures for training datasets, checkpointing, inference artifacts, and shared research workflows\n\n - Deploy and tune parallel filesystems, object storage, and local NVMe caching for demanding AI workloads\n\n - Benchmark throughput, latency, metadata performance, and concurrent access with representative training and checkpoint workloads\n\n - Build provisioning, capacity planning, lifecycle management, and operational automation for storage services\n\n - Design and test replication, recovery, backup, and failure-handling procedures with explicit durability and availability targets\n\n - Diagnose performance and reliability issues across applications, clients, networks, filesystems, and devices\n\n - Implement access controls, tenant separation, quotas, monitoring, and runbooks; collaborate with compute and networking teams\n\n\nTECHNICAL REQUIREMENTS\n\n\nREQUIRED EXPERIENCE\n\n - 3+ years building or operating production distributed storage systems\n\n - Hands-on experience with at least one parallel or distributed filesystem or object storage platform, such as Lustre, BeeGFS, Ceph, or GPFS\n\n - Strong Linux administration and performance troubleshooting skills\n\n - Experience automating infrastructure operations in Python, Go, Bash, or similar languages\n\n - Understanding of storage failure modes, data integrity, consistency, replication, and recovery\n\n\nINFRASTRUCTURE SKILLS\n\n - Block, file, and object storage semantics and their performance tradeoffs\n\n - NVMe/SSD performance, filesystem tuning, I/O profiling, and benchmarking\n\n - High-throughput storage networking and distributed client behavior\n\n - Capacity forecasting, observability, alerting, and safe maintenance procedures\n\n - Authentication, authorization, encryption, and secure data lifecycle management\n\n\nNICE TO HAVE\n\n - Experience supporting large GPU training clusters and high-volume checkpoint workloads\n\n - S3-compatible object storage, data tiering, or distributed caching\n\n - RDMA-enabled storage or GPUDirect Storage experience\n\n - Kubernetes storage integrations or SLURM environments\n\n - Storage cost optimization and contributions to open-source storage systems\n\n\nGROWTH OPPORTUNITY\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\n\nCOMPENSATION\n\nCash compensation range of $150,000–$300,000 plus equity incentives."},{"id":"6a4c3f0f-d411-4e12-9ea6-afede818ce16","title":"Member of Technical Staff - Datacenter Operations","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[{"location":"Remote","address":{"postalAddress":{"addressCountry":"United States"}}}],"publishedAt":"2026-09-17T22:47:56.714+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/6a4c3f0f-d411-4e12-9ea6-afede818ce16","applyUrl":"https://jobs.ashbyhq.com/primeintellect/6a4c3f0f-d411-4e12-9ea6-afede818ce16/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><h2>Role Impact</h2><p style=\"min-height:1.5em\">You'll own the operational readiness of the physical infrastructure behind our GPU cloud. Coordinate deployments, hardware maintenance, and incident response with datacenter partners, turning new capacity into dependable production infrastructure and reducing time to repair.</p><h2>Core Technical Responsibilities</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Coordinate rack deployment, cabling, inventory, and acceptance testing for new GPU capacity with datacenter partners and engineering teams</p></li><li><p style=\"min-height:1.5em\">Maintain accurate asset records, rack layouts, power allocations, cabling documentation, and spare-parts inventories</p></li><li><p style=\"min-height:1.5em\">Lead hardware fault triage and coordinate remote hands, vendor escalations, component replacement, and RMA workflows</p></li><li><p style=\"min-height:1.5em\">Establish maintenance plans and change procedures that minimize customer disruption and protect equipment and data</p></li><li><p style=\"min-height:1.5em\">Track capacity readiness, hardware failure trends, repair times, and operational risks; automate repetitive reporting and workflows</p></li><li><p style=\"min-height:1.5em\">Partner with facility teams on power, cooling, environmental monitoring, and readiness for high-density GPU deployments</p></li><li><p style=\"min-height:1.5em\">Create runbooks and escalation procedures and support incident response across datacenter and infrastructure teams</p></li></ul><h2>Technical Requirements</h2><h3>Required Experience</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">3+ years in datacenter operations, hardware infrastructure, or production systems operations</p></li><li><p style=\"min-height:1.5em\">Hands-on experience deploying and troubleshooting rack-mounted servers, networking equipment, and structured cabling</p></li><li><p style=\"min-height:1.5em\">Experience coordinating datacenter providers, remote hands, and hardware vendors through deployments and incidents</p></li><li><p style=\"min-height:1.5em\">Working knowledge of Linux diagnostics, BMC consoles, and server hardware health tools</p></li><li><p style=\"min-height:1.5em\">Strong operational judgment, documentation habits, and ownership of issues through resolution</p></li></ul><h3>Infrastructure Skills</h3><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">GPU server components, PCIe devices, memory, storage, and hardware diagnostics</p></li><li><p style=\"min-height:1.5em\">Rack power budgeting, redundant power paths, airflow, and high-density cooling fundamentals</p></li><li><p style=\"min-height:1.5em\">Fiber and copper cabling, optics, labeling, and physical network troubleshooting</p></li><li><p style=\"min-height:1.5em\">Asset tracking, spares management, change control, and incident management</p></li><li><p style=\"min-height:1.5em\">Basic scripting for inventory, health checks, and operational automation; familiarity with safe datacenter working practices</p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with NVIDIA DGX/HGX systems or large GPU cluster deployments</p></li><li><p style=\"min-height:1.5em\">Liquid-cooled infrastructure and coordination with facility engineering teams</p></li><li><p style=\"min-height:1.5em\">Experience bringing up new datacenter sites or expanding multi-site capacity</p></li><li><p style=\"min-height:1.5em\">Hardware qualification, burn-in testing, and reliability analysis</p></li><li><p style=\"min-height:1.5em\">Experience integrating physical operations with automated fleet provisioning</p></li></ul><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.</p><p style=\"min-height:1.5em\">We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.</p><p style=\"min-height:1.5em\">Apply now and join us in our mission to democratize access to planetary scale computing.</p><h2>Compensation</h2><p style=\"min-height:1.5em\">Cash compensation range of $150,000–$300,000 plus equity incentives.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\nROLE IMPACT\n\nYou'll own the operational readiness of the physical infrastructure behind our GPU cloud. Coordinate deployments, hardware maintenance, and incident response with datacenter partners, turning new capacity into dependable production infrastructure and reducing time to repair.\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n - Coordinate rack deployment, cabling, inventory, and acceptance testing for new GPU capacity with datacenter partners and engineering teams\n\n - Maintain accurate asset records, rack layouts, power allocations, cabling documentation, and spare-parts inventories\n\n - Lead hardware fault triage and coordinate remote hands, vendor escalations, component replacement, and RMA workflows\n\n - Establish maintenance plans and change procedures that minimize customer disruption and protect equipment and data\n\n - Track capacity readiness, hardware failure trends, repair times, and operational risks; automate repetitive reporting and workflows\n\n - Partner with facility teams on power, cooling, environmental monitoring, and readiness for high-density GPU deployments\n\n - Create runbooks and escalation procedures and support incident response across datacenter and infrastructure teams\n\n\nTECHNICAL REQUIREMENTS\n\n\nREQUIRED EXPERIENCE\n\n - 3+ years in datacenter operations, hardware infrastructure, or production systems operations\n\n - Hands-on experience deploying and troubleshooting rack-mounted servers, networking equipment, and structured cabling\n\n - Experience coordinating datacenter providers, remote hands, and hardware vendors through deployments and incidents\n\n - Working knowledge of Linux diagnostics, BMC consoles, and server hardware health tools\n\n - Strong operational judgment, documentation habits, and ownership of issues through resolution\n\n\nINFRASTRUCTURE SKILLS\n\n - GPU server components, PCIe devices, memory, storage, and hardware diagnostics\n\n - Rack power budgeting, redundant power paths, airflow, and high-density cooling fundamentals\n\n - Fiber and copper cabling, optics, labeling, and physical network troubleshooting\n\n - Asset tracking, spares management, change control, and incident management\n\n - Basic scripting for inventory, health checks, and operational automation; familiarity with safe datacenter working practices\n\n\nNICE TO HAVE\n\n - Experience with NVIDIA DGX/HGX systems or large GPU cluster deployments\n\n - Liquid-cooled infrastructure and coordination with facility engineering teams\n\n - Experience bringing up new datacenter sites or expanding multi-site capacity\n\n - Hardware qualification, burn-in testing, and reliability analysis\n\n - Experience integrating physical operations with automated fleet provisioning\n\n\nGROWTH OPPORTUNITY\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\n\nCOMPENSATION\n\nCash compensation range of $150,000–$300,000 plus equity incentives."},{"id":"3e11ec2c-34c1-45c8-a732-ab3001225f25","title":"Senior Technical Partnerships Manager","department":"Growth","team":"Growth","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-10-08T18:46:20.266+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/3e11ec2c-34c1-45c8-a732-ab3001225f25","applyUrl":"https://jobs.ashbyhq.com/primeintellect/3e11ec2c-34c1-45c8-a732-ab3001225f25/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2>Your Role</h2><p style=\"min-height:1.5em\">No one builds the AI infrastructure stack alone. The GPU makers, cloud and datacenter providers, model labs, and enterprise platforms we work with are core to how we reach customers and how we ship. The partnerships that matter in this industry are not logos on a slide — they are shipped integrations, field teams that can actually sell and support a joint solution, and customers who win because both companies showed up together. Very few people know how to make those partnerships real at the technical and commercial level simultaneously.</p><p style=\"min-height:1.5em\">You will own our most strategic technical alliances end to end: NVIDIA, hyperscalers, neoclouds, datacenter operators, and the next wave of partners across models, tooling, and enterprise. You will be the person a partner's engineering, product, and field teams trust to turn a signed MOU into something that moves pipeline and ships product.</p><p style=\"min-height:1.5em\">The work sits at the intersection of technical depth and commercial execution. You will go deep enough on GPUs, networking, distributed training, and inference stacks to hold your own with partner engineers, and broad enough to run joint go-to-market, executive relationships, and a scalable partner program. You will scope proofs of concept with joint customers, build the enablement that lets partner sellers position us, secure marketplace and co-sell motions, and bring partner roadmaps back into our product and research decisions.</p><p style=\"min-height:1.5em\">The partnerships you build will directly shape how Prime Intellect reaches the labs, enterprises, and research teams building on our stack — and how fast we can deliver compute, training, and environments to them.</p><p style=\"min-height:1.5em\"></p><h2>Responsibilities</h2><p style=\"min-height:1.5em\"><strong>Partner Relationship Management</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own 3–5 tier-1 technical partnerships (e.g., NVIDIA, hyperscalers, neoclouds, datacenter operators) as the single accountable lead</p></li><li><p style=\"min-height:1.5em\">Build relationships across the partner org at every level: alliance managers, developer relations, product and engineering, field sales, and executives</p></li><li><p style=\"min-height:1.5em\">Run quarterly business reviews and set joint annual plans with clear goals, owners, and metrics</p></li><li><p style=\"min-height:1.5em\">Navigate partner programs (e.g., NVIDIA Inception, NPN, cloud marketplace and co-sell programs) to unlock credits, benefits, tiering, and visibility</p></li><li><p style=\"min-height:1.5em\">Negotiate and manage partnership agreements, MOUs, and joint commitments with Legal and Finance</p></li></ul><p style=\"min-height:1.5em\"><strong>Joint Customer Engagement</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Lead and join joint customer calls with partner account teams, from discovery through technical deep dives and close</p></li><li><p style=\"min-height:1.5em\">Act as the technical bridge in deals: map customer workloads to the joint solution, scope proofs of concept, and remove blockers</p></li><li><p style=\"min-height:1.5em\">Coordinate escalations across both companies when joint customers hit issues</p></li><li><p style=\"min-height:1.5em\">Build a pipeline of partner-sourced and partner-influenced opportunities, and report on it</p></li></ul><p style=\"min-height:1.5em\"><strong>Technical Integration &amp; Product Feedback</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Drive joint technical work: integrations, benchmarks, validated configurations, certifications, and optimizations on partner hardware and software</p></li><li><p style=\"min-height:1.5em\">Get early access to partner roadmaps, hardware, and SDKs, and translate them into product opportunities for us</p></li><li><p style=\"min-height:1.5em\">Bring partner and customer feedback into our product and research roadmaps, and advocate for our needs in the partner's roadmap</p></li><li><p style=\"min-height:1.5em\">Write or co-author reference architectures, technical blog posts, and solution briefs</p></li></ul><p style=\"min-height:1.5em\"><strong>Training &amp; Enablement</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build enablement content for partner field teams: pitch decks, battlecards, demo scripts, reference architectures, and FAQs</p></li><li><p style=\"min-height:1.5em\">Deliver live and recorded training to partner sellers, solution architects, and support engineers so they can position, sell, and troubleshoot our products</p></li><li><p style=\"min-height:1.5em\">Enable our own team on partner products, roadmaps, and programs</p></li><li><p style=\"min-height:1.5em\">Track enablement reach and impact: people trained, certified, and actively co-selling</p></li></ul><p style=\"min-height:1.5em\"><strong>Joint Go-to-Market &amp; Marketing</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Plan co-marketing: launches, case studies, webinars, joint press, and partner showcase placements</p></li><li><p style=\"min-height:1.5em\">Represent Prime Intellect at partner events and industry conferences (e.g., NVIDIA GTC), including talks, booths, and customer meetings</p></li><li><p style=\"min-height:1.5em\">Secure marketplace listings and co-sell motions with cloud and channel partners</p></li></ul><p style=\"min-height:1.5em\"><strong>Partner Program &amp; Strategy</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Identify and evaluate new strategic partners across compute, models, tooling, and enterprise</p></li><li><p style=\"min-height:1.5em\">Design a scalable partner program: tiers, benefits, onboarding, and playbooks</p></li><li><p style=\"min-height:1.5em\">Own partnership metrics and report regularly to leadership on revenue impact, pipeline, and technical milestones</p></li></ul><p style=\"min-height:1.5em\"></p><h2>What We're Looking For</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">7+ years in technical partnerships, alliances, solutions architecture, or technical business development, with at least 3 years managing strategic partners</p></li><li><p style=\"min-height:1.5em\">Direct experience working with NVIDIA, a hyperscaler (AWS, GCP, Azure), or a GPU cloud provider — ideally on the partner side of that relationship</p></li><li><p style=\"min-height:1.5em\">Strong technical grounding in AI infrastructure: GPUs and accelerators, networking (InfiniBand, RoCE), distributed training and inference, and the CUDA and PyTorch ecosystem</p></li><li><p style=\"min-height:1.5em\">A track record of co-selling — you've run joint customer calls and closed or influenced deals alongside partner field teams</p></li><li><p style=\"min-height:1.5em\">Experience building and delivering technical enablement to sales and engineering audiences</p></li><li><p style=\"min-height:1.5em\">Comfortable presenting to executives, engineers, and conference audiences</p></li><li><p style=\"min-height:1.5em\">Able to run a complex, multi-stakeholder relationship with little oversight, and to say no when a joint initiative isn't worth it</p></li><li><p style=\"min-height:1.5em\">Clear, concise writer: plans, briefs, and technical docs</p></li><li><p style=\"min-height:1.5em\">High ownership — you see gaps and build the fix before anyone asks</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Prior experience inside NVIDIA's partner or developer ecosystem, or inside a hyperscaler's AI/ML partner organization</p></li><li><p style=\"min-height:1.5em\">Hands-on background as a solutions architect or ML engineer before moving into partnerships</p></li><li><p style=\"min-height:1.5em\">Experience standing up a partner program from scratch at an early-stage infrastructure company</p></li><li><p style=\"min-height:1.5em\">Existing relationships with alliance, field, and engineering teams at major compute providers</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Why This Role</h2><p style=\"min-height:1.5em\">The AI infrastructure ecosystem is being assembled right now, and the partnerships that define it are still being written. You'll own the relationships that determine how Prime Intellect reaches the market, work directly with leadership and the engineering team on what we build and with whom, and sit in the room with partner executives and engineers at the companies shaping the next decade of compute. The network and expertise you build here are increasingly rare and valuable across the industry.</p><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation range of $250–300k + meaningful equity</p></li><li><p style=\"min-height:1.5em\">San Francisco or New York, with travel to partner sites, customer meetings, and conferences (about 25–30%)</p></li><li><p style=\"min-height:1.5em\">Visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nNo one builds the AI infrastructure stack alone. The GPU makers, cloud and datacenter providers, model labs, and enterprise platforms we work with are core to how we reach customers and how we ship. The partnerships that matter in this industry are not logos on a slide — they are shipped integrations, field teams that can actually sell and support a joint solution, and customers who win because both companies showed up together. Very few people know how to make those partnerships real at the technical and commercial level simultaneously.\n\nYou will own our most strategic technical alliances end to end: NVIDIA, hyperscalers, neoclouds, datacenter operators, and the next wave of partners across models, tooling, and enterprise. You will be the person a partner's engineering, product, and field teams trust to turn a signed MOU into something that moves pipeline and ships product.\n\nThe work sits at the intersection of technical depth and commercial execution. You will go deep enough on GPUs, networking, distributed training, and inference stacks to hold your own with partner engineers, and broad enough to run joint go-to-market, executive relationships, and a scalable partner program. You will scope proofs of concept with joint customers, build the enablement that lets partner sellers position us, secure marketplace and co-sell motions, and bring partner roadmaps back into our product and research decisions.\n\nThe partnerships you build will directly shape how Prime Intellect reaches the labs, enterprises, and research teams building on our stack — and how fast we can deliver compute, training, and environments to them.\n\n\n\n\nRESPONSIBILITIES\n\nPartner Relationship Management\n\n - Own 3–5 tier-1 technical partnerships (e.g., NVIDIA, hyperscalers, neoclouds, datacenter operators) as the single accountable lead\n\n - Build relationships across the partner org at every level: alliance managers, developer relations, product and engineering, field sales, and executives\n\n - Run quarterly business reviews and set joint annual plans with clear goals, owners, and metrics\n\n - Navigate partner programs (e.g., NVIDIA Inception, NPN, cloud marketplace and co-sell programs) to unlock credits, benefits, tiering, and visibility\n\n - Negotiate and manage partnership agreements, MOUs, and joint commitments with Legal and Finance\n\nJoint Customer Engagement\n\n - Lead and join joint customer calls with partner account teams, from discovery through technical deep dives and close\n\n - Act as the technical bridge in deals: map customer workloads to the joint solution, scope proofs of concept, and remove blockers\n\n - Coordinate escalations across both companies when joint customers hit issues\n\n - Build a pipeline of partner-sourced and partner-influenced opportunities, and report on it\n\nTechnical Integration & Product Feedback\n\n - Drive joint technical work: integrations, benchmarks, validated configurations, certifications, and optimizations on partner hardware and software\n\n - Get early access to partner roadmaps, hardware, and SDKs, and translate them into product opportunities for us\n\n - Bring partner and customer feedback into our product and research roadmaps, and advocate for our needs in the partner's roadmap\n\n - Write or co-author reference architectures, technical blog posts, and solution briefs\n\nTraining & Enablement\n\n - Build enablement content for partner field teams: pitch decks, battlecards, demo scripts, reference architectures, and FAQs\n\n - Deliver live and recorded training to partner sellers, solution architects, and support engineers so they can position, sell, and troubleshoot our products\n\n - Enable our own team on partner products, roadmaps, and programs\n\n - Track enablement reach and impact: people trained, certified, and actively co-selling\n\nJoint Go-to-Market & Marketing\n\n - Plan co-marketing: launches, case studies, webinars, joint press, and partner showcase placements\n\n - Represent Prime Intellect at partner events and industry conferences (e.g., NVIDIA GTC), including talks, booths, and customer meetings\n\n - Secure marketplace listings and co-sell motions with cloud and channel partners\n\nPartner Program & Strategy\n\n - Identify and evaluate new strategic partners across compute, models, tooling, and enterprise\n\n - Design a scalable partner program: tiers, benefits, onboarding, and playbooks\n\n - Own partnership metrics and report regularly to leadership on revenue impact, pipeline, and technical milestones\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - 7+ years in technical partnerships, alliances, solutions architecture, or technical business development, with at least 3 years managing strategic partners\n\n - Direct experience working with NVIDIA, a hyperscaler (AWS, GCP, Azure), or a GPU cloud provider — ideally on the partner side of that relationship\n\n - Strong technical grounding in AI infrastructure: GPUs and accelerators, networking (InfiniBand, RoCE), distributed training and inference, and the CUDA and PyTorch ecosystem\n\n - A track record of co-selling — you've run joint customer calls and closed or influenced deals alongside partner field teams\n\n - Experience building and delivering technical enablement to sales and engineering audiences\n\n - Comfortable presenting to executives, engineers, and conference audiences\n\n - Able to run a complex, multi-stakeholder relationship with little oversight, and to say no when a joint initiative isn't worth it\n\n - Clear, concise writer: plans, briefs, and technical docs\n\n - High ownership — you see gaps and build the fix before anyone asks\n\n - AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster\n\n\n\nBonus:\n\n - Prior experience inside NVIDIA's partner or developer ecosystem, or inside a hyperscaler's AI/ML partner organization\n\n - Hands-on background as a solutions architect or ML engineer before moving into partnerships\n\n - Experience standing up a partner program from scratch at an early-stage infrastructure company\n\n - Existing relationships with alliance, field, and engineering teams at major compute providers\n\n\n\n\nWHY THIS ROLE\n\nThe AI infrastructure ecosystem is being assembled right now, and the partnerships that define it are still being written. You'll own the relationships that determine how Prime Intellect reaches the market, work directly with leadership and the engineering team on what we build and with whom, and sit in the room with partner executives and engineers at the companies shaping the next decade of compute. The network and expertise you build here are increasingly rare and valuable across the industry.\n\n\n\n\nWHAT WE OFFER\n\n - Cash compensation range of $250–300k + meaningful equity\n\n - San Francisco or New York, with travel to partner sites, customer meetings, and conferences (about 25–30%)\n\n - Visa sponsorship and relocation support\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"4cd01364-d7b4-4cb0-b299-a5e839b36995","title":"People Operations Coordinator","department":"Finance / Operations","team":"Finance / Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-10-08T18:58:08.002+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/4cd01364-d7b4-4cb0-b299-a5e839b36995","applyUrl":"https://jobs.ashbyhq.com/primeintellect/4cd01364-d7b4-4cb0-b299-a5e839b36995/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.</p><p style=\"min-height:1.5em\">Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.</p><p style=\"min-height:1.5em\">Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.</p><p style=\"min-height:1.5em\"></p><h2>Your Role</h2><p style=\"min-height:1.5em\">We are a team of about 60, split between our San Francisco office and remote staff, and we are hiring quickly. Every researcher, engineer, and operator who joins us has a first day, a first week, and a first impression of how seriously we take the people who build here. Right now, that experience depends on a lot of people doing a lot of small things right. This role makes it a system.</p><p style=\"min-height:1.5em\">You will own the employee lifecycle from the moment a candidate is scheduled for an interview through a new hire's first weeks. You will design every new hire's first day, run onboarding end to end, coordinate recruiting logistics across multiple open searches, and help bring the team together in person. You will also be the person who looks at how this function works and makes it faster, more reliable, and more personal — including where AI tools and automation can take the repetitive parts off your plate so you can spend your time on the parts that only a person can do.</p><p style=\"min-height:1.5em\">This is an in-person role based in our San Francisco office, reporting to our Executive Business Partner and working closely with the Head of Talent, hiring managers, IT, and finance.</p><p style=\"min-height:1.5em\"></p><h2>Responsibilities</h2><p style=\"min-height:1.5em\"><strong>Onboarding &amp; Employee Experience</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Design the first-day schedule and experience for every new hire so they feel welcomed and productive from day one, with a white-glove approach for executive hires</p></li><li><p style=\"min-height:1.5em\">Set up desks and equipment before day one: laptop, monitor, welcome kit in place; coordinate provisioning, accounts, and tool access with IT</p></li><li><p style=\"min-height:1.5em\">Coordinate finance onboarding — payroll, benefits enrollment, expense tools, company card — and office access: door access, building entry, and meal program</p></li><li><p style=\"min-height:1.5em\">Complete required onboarding steps accurately and on time: background checks, I-9 verification, employee records, and HRIS setup</p></li><li><p style=\"min-height:1.5em\">Identify immigration and visa needs early, route them to the right people, and track them to resolution</p></li><li><p style=\"min-height:1.5em\">Maintain and continuously improve the onboarding system so every hire gets a consistent, well-run first week</p></li><li><p style=\"min-height:1.5em\">Support offboarding: recover equipment and remove access</p></li></ul><p style=\"min-height:1.5em\"><strong>Recruiting Coordination</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Own interview scheduling across multiple open roles so every candidate and interviewer shows up informed, prepared, and on time</p></li><li><p style=\"min-height:1.5em\">Book travel and host candidates for onsite interviews and work trials, creating a warm, human candidate experience</p></li><li><p style=\"min-height:1.5em\">Keep candidates and hiring teams informed throughout the process with timely, clear communication</p></li><li><p style=\"min-height:1.5em\">Maintain Ashby as the single source of truth: stage updates, candidate notes, and pipeline hygiene</p></li><li><p style=\"min-height:1.5em\">Own scheduling timelines and SLAs, surface risks early, and keep recruiters and hiring managers in the loop</p></li></ul><p style=\"min-height:1.5em\"><strong>Systems, Culture &amp; Team Operations</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Find smarter, faster ways to run this function, including automating repetitive work with AI tools</p></li><li><p style=\"min-height:1.5em\">Track open hiring and onboarding tasks and follow through on every commitment</p></li><li><p style=\"min-height:1.5em\">Contribute to an in-person culture that builds connection across in-office and remote teams</p></li><li><p style=\"min-height:1.5em\">Help plan and run team onsites and offsites, including attendee logistics and travel</p></li><li><p style=\"min-height:1.5em\">Take on recruiting operations and sourcing projects as the function grows</p></li></ul><h2>What Success Looks Like</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">New hires feel expected and cared for. Before day one, they know where to go, what to expect, and who to ask for help.</p></li><li><p style=\"min-height:1.5em\">Laptops arrive on time, accounts work, schedules are clear, and first-week travel is arranged. You check directly with each new hire rather than assuming everything is set.</p></li><li><p style=\"min-height:1.5em\">Compliance steps — background checks, I-9s, records — are complete and accurate without anyone having to chase them.</p></li><li><p style=\"min-height:1.5em\">Recruiting, IT, managers, and office teams know what they own. You spot delays and resolve them before they affect a start date.</p></li><li><p style=\"min-height:1.5em\">Trackers, checklists, and communications stay current as hiring volume grows.</p></li></ul><h2>What We're Looking For</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">2+ years in recruiting coordination, people operations, HR, or a similar high-volume coordination role</p></li><li><p style=\"min-height:1.5em\">Proactive coordination: you can juggle many starts, owners, and deadlines without losing the details, and you follow up before anyone has to ask</p></li><li><p style=\"min-height:1.5em\">Real care for the employee and candidate experience — a warm welcome is built from both thoughtful communication and reliable execution</p></li><li><p style=\"min-height:1.5em\">Comfort managing background checks, I-9 verification, employee records, and HRIS setup, and handling sensitive information with discretion, including for senior and executive candidates</p></li><li><p style=\"min-height:1.5em\">Cross-functional follow-through: you make ownership clear and stay with an issue until it's resolved</p></li><li><p style=\"min-height:1.5em\">Process improvement instinct: you spot recurring gaps in a checklist, handoff, or message and fix them</p></li><li><p style=\"min-height:1.5em\">Highly skilled in tools like Google Calendar, Slack, and Notion, with demonstrated ability to handle high-volume work efficiently</p></li><li><p style=\"min-height:1.5em\">AI-native in how you work: you use LLMs and automation to take repetitive work off your plate</p></li><li><p style=\"min-height:1.5em\">Low ego, high ownership — as willing to improve a workflow as to track down a delayed laptop</p></li><li><p style=\"min-height:1.5em\">Able to work in person in our San Francisco office</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience with Ashby or another modern applicant tracking system</p></li><li><p style=\"min-height:1.5em\">Experience running onboarding at a fast-growing startup</p></li><li><p style=\"min-height:1.5em\">Experience coordinating immigration or visa processes with outside counsel</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Why This Role</h2><p style=\"min-height:1.5em\">You will shape how every person who joins Prime Intellect experiences their first weeks, at a company where the people being onboarded are among the best researchers and engineers in the world. You will build the people operations foundation from an early stage, work directly with leadership and the Head of Talent, and have real room to grow into recruiting operations, people operations, or wherever your strengths take you as the company scales.</p><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">$90,000–$120,000 base salary + equity</p></li><li><p style=\"min-height:1.5em\">In-person role in our San Francisco office (501 Folsom St)</p></li><li><p style=\"min-height:1.5em\">Professional development budget</p></li><li><p style=\"min-height:1.5em\">Team off-sites and conferences</p></li><li><p style=\"min-height:1.5em\">A front-row seat to building the infrastructure layer for open AI</p></li></ul>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nWe are a team of about 60, split between our San Francisco office and remote staff, and we are hiring quickly. Every researcher, engineer, and operator who joins us has a first day, a first week, and a first impression of how seriously we take the people who build here. Right now, that experience depends on a lot of people doing a lot of small things right. This role makes it a system.\n\nYou will own the employee lifecycle from the moment a candidate is scheduled for an interview through a new hire's first weeks. You will design every new hire's first day, run onboarding end to end, coordinate recruiting logistics across multiple open searches, and help bring the team together in person. You will also be the person who looks at how this function works and makes it faster, more reliable, and more personal — including where AI tools and automation can take the repetitive parts off your plate so you can spend your time on the parts that only a person can do.\n\nThis is an in-person role based in our San Francisco office, reporting to our Executive Business Partner and working closely with the Head of Talent, hiring managers, IT, and finance.\n\n\n\n\nRESPONSIBILITIES\n\nOnboarding & Employee Experience\n\n - Design the first-day schedule and experience for every new hire so they feel welcomed and productive from day one, with a white-glove approach for executive hires\n\n - Set up desks and equipment before day one: laptop, monitor, welcome kit in place; coordinate provisioning, accounts, and tool access with IT\n\n - Coordinate finance onboarding — payroll, benefits enrollment, expense tools, company card — and office access: door access, building entry, and meal program\n\n - Complete required onboarding steps accurately and on time: background checks, I-9 verification, employee records, and HRIS setup\n\n - Identify immigration and visa needs early, route them to the right people, and track them to resolution\n\n - Maintain and continuously improve the onboarding system so every hire gets a consistent, well-run first week\n\n - Support offboarding: recover equipment and remove access\n\nRecruiting Coordination\n\n - Own interview scheduling across multiple open roles so every candidate and interviewer shows up informed, prepared, and on time\n\n - Book travel and host candidates for onsite interviews and work trials, creating a warm, human candidate experience\n\n - Keep candidates and hiring teams informed throughout the process with timely, clear communication\n\n - Maintain Ashby as the single source of truth: stage updates, candidate notes, and pipeline hygiene\n\n - Own scheduling timelines and SLAs, surface risks early, and keep recruiters and hiring managers in the loop\n\nSystems, Culture & Team Operations\n\n - Find smarter, faster ways to run this function, including automating repetitive work with AI tools\n\n - Track open hiring and onboarding tasks and follow through on every commitment\n\n - Contribute to an in-person culture that builds connection across in-office and remote teams\n\n - Help plan and run team onsites and offsites, including attendee logistics and travel\n\n - Take on recruiting operations and sourcing projects as the function grows\n\n\nWHAT SUCCESS LOOKS LIKE\n\n - New hires feel expected and cared for. Before day one, they know where to go, what to expect, and who to ask for help.\n\n - Laptops arrive on time, accounts work, schedules are clear, and first-week travel is arranged. You check directly with each new hire rather than assuming everything is set.\n\n - Compliance steps — background checks, I-9s, records — are complete and accurate without anyone having to chase them.\n\n - Recruiting, IT, managers, and office teams know what they own. You spot delays and resolve them before they affect a start date.\n\n - Trackers, checklists, and communications stay current as hiring volume grows.\n\n\nWHAT WE'RE LOOKING FOR\n\n - 2+ years in recruiting coordination, people operations, HR, or a similar high-volume coordination role\n\n - Proactive coordination: you can juggle many starts, owners, and deadlines without losing the details, and you follow up before anyone has to ask\n\n - Real care for the employee and candidate experience — a warm welcome is built from both thoughtful communication and reliable execution\n\n - Comfort managing background checks, I-9 verification, employee records, and HRIS setup, and handling sensitive information with discretion, including for senior and executive candidates\n\n - Cross-functional follow-through: you make ownership clear and stay with an issue until it's resolved\n\n - Process improvement instinct: you spot recurring gaps in a checklist, handoff, or message and fix them\n\n - Highly skilled in tools like Google Calendar, Slack, and Notion, with demonstrated ability to handle high-volume work efficiently\n\n - AI-native in how you work: you use LLMs and automation to take repetitive work off your plate\n\n - Low ego, high ownership — as willing to improve a workflow as to track down a delayed laptop\n\n - Able to work in person in our San Francisco office\n\nBonus:\n\n - Experience with Ashby or another modern applicant tracking system\n\n - Experience running onboarding at a fast-growing startup\n\n - Experience coordinating immigration or visa processes with outside counsel\n\n\n\n\nWHY THIS ROLE\n\nYou will shape how every person who joins Prime Intellect experiences their first weeks, at a company where the people being onboarded are among the best researchers and engineers in the world. You will build the people operations foundation from an early stage, work directly with leadership and the Head of Talent, and have real room to grow into recruiting operations, people operations, or wherever your strengths take you as the company scales.\n\n\n\n\nWHAT WE OFFER\n\n - $90,000–$120,000 base salary + equity\n\n - In-person role in our San Francisco office (501 Folsom St)\n\n - Professional development budget\n\n - Team off-sites and conferences\n\n - A front-row seat to building the infrastructure layer for open AI"},{"id":"ae969ec1-0f44-4289-9797-a880b05db389","title":"Member of Technical Staff - Production Engineering","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-10-09T22:36:11.481+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/primeintellect/ae969ec1-0f44-4289-9797-a880b05db389","applyUrl":"https://jobs.ashbyhq.com/primeintellect/ae969ec1-0f44-4289-9797-a880b05db389/application","descriptionHtml":"<h2>Own Your Intelligence</h2><p style=\"min-height:1.5em\">Prime Intellect is building the open superintelligence stack: infrastructure and tools that help ambitious AI teams train, evaluate, and deploy advanced models.</p><p style=\"min-height:1.5em\"></p><h2>Role Impact</h2><p style=\"min-height:1.5em\">Platform engineering at Prime Intellect sits on the path from a research idea to a running AI workload. Your core mandate is to make every engineering team faster and safer: turn recurring infrastructure and security needs into paved roads, self-service capabilities, and guardrails that help teams move from idea to production with confidence.</p><p style=\"min-height:1.5em\">This is a hands-on senior role with broad technical ownership. You will write code, set platform standards, and partner directly with research, product engineering, and security to improve how services are built, shipped, and operated.</p><p style=\"min-height:1.5em\"></p><h2>Why This Role Stands Out</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Work at the intersection of cloud infrastructure and distributed, GPU-intensive AI workloads</p></li><li><p style=\"min-height:1.5em\">Own foundational systems in a small, senior team where technical decisions have visible impact</p></li><li><p style=\"min-height:1.5em\">Multiply the impact of other teams through secure defaults, automation, and a strong developer experience</p><p style=\"min-height:1.5em\"></p></li></ul><h2>What You’ll Own</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build reusable infrastructure-as-code and reliable CI/CD workflows for platform services</p></li><li><p style=\"min-height:1.5em\">Design cloud foundations spanning compute, networking, identity, secrets, and service delivery</p></li><li><p style=\"min-height:1.5em\">Develop progressive rollout, health-check, and rollback patterns for critical infrastructure</p></li><li><p style=\"min-height:1.5em\">Build self-service platform capabilities, templates, and guardrails that shorten the path from code to production</p></li><li><p style=\"min-height:1.5em\">Partner with research and product teams to remove delivery bottlenecks and turn recurring needs into reusable platform capabilities</p></li><li><p style=\"min-height:1.5em\">Define practical observability standards across metrics, logs, dashboards, and alerting using tools such as Grafana</p></li><li><p style=\"min-height:1.5em\">Define and own platform SLOs, partnering with service teams on targets, error budgets, and reliability priorities</p></li><li><p style=\"min-height:1.5em\">Turn security and compliance requirements into reusable platform controls</p></li><li><p style=\"min-height:1.5em\">Lead complex platform projects from technical design through adoption and steady-state operation</p><p style=\"min-height:1.5em\"></p></li></ul><h2>What We’re Looking For</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">5+ years in infrastructure, platform, or security-focused engineering</p></li><li><p style=\"min-height:1.5em\">Deep hands-on experience with Terraform or similar infrastructure-as-code tooling</p></li><li><p style=\"min-height:1.5em\">Strong knowledge of cloud networking, IAM, secrets management, and CI/CD</p></li><li><p style=\"min-height:1.5em\">Experience designing secure software delivery lifecycle environments from development through production</p></li><li><p style=\"min-height:1.5em\">Production experience with Kubernetes or similar container orchestration platforms</p></li><li><p style=\"min-height:1.5em\">Ability to debug across infrastructure layers and make sound trade-offs under ambiguity</p></li><li><p style=\"min-height:1.5em\">Clear technical communication and a track record of leading cross-functional projects</p><p style=\"min-height:1.5em\"></p></li></ul><h2>Nice to Have</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience operating ML/LLM training or inference infrastructure</p></li><li><p style=\"min-height:1.5em\">Exposure to GPU infrastructure and distributed systems</p></li><li><p style=\"min-height:1.5em\">Experience with zero-trust access patterns</p></li><li><p style=\"min-height:1.5em\">Experience supporting compliance or audit-readiness programs</p></li></ul><p style=\"min-height:1.5em\"></p><h2>What We Offer</h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Cash compensation $150K–$300K with significant equity</p></li><li><p style=\"min-height:1.5em\">Flexible work arrangement (remote or San Francisco office)</p></li><li><p style=\"min-height:1.5em\">Full visa sponsorship and relocation support</p></li><li><p style=\"min-height:1.5em\">Professional development budget for courses and conferences</p></li><li><p style=\"min-height:1.5em\">Regular team off-sites and conference attendance</p></li></ul><p style=\"min-height:1.5em\"></p><h2>Growth Opportunity</h2><p style=\"min-height:1.5em\">You’ll have direct influence over the platform behind open frontier AI research and products used by ambitious AI teams. Your impact will show up in faster delivery, safer operations, and less infrastructure work repeated across teams. We value ownership, technical judgment, and engineers who turn complex problems into simple, durable systems.</p>","descriptionPlain":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: infrastructure and tools that help ambitious AI teams train, evaluate, and deploy advanced models.\n\n\n\n\nROLE IMPACT\n\nPlatform engineering at Prime Intellect sits on the path from a research idea to a running AI workload. Your core mandate is to make every engineering team faster and safer: turn recurring infrastructure and security needs into paved roads, self-service capabilities, and guardrails that help teams move from idea to production with confidence.\n\nThis is a hands-on senior role with broad technical ownership. You will write code, set platform standards, and partner directly with research, product engineering, and security to improve how services are built, shipped, and operated.\n\n\n\n\nWHY THIS ROLE STANDS OUT\n\n - Work at the intersection of cloud infrastructure and distributed, GPU-intensive AI workloads\n\n - Own foundational systems in a small, senior team where technical decisions have visible impact\n\n - Multiply the impact of other teams through secure defaults, automation, and a strong developer experience\n   \n   \n\n\nWHAT YOU’LL OWN\n\n - Build reusable infrastructure-as-code and reliable CI/CD workflows for platform services\n\n - Design cloud foundations spanning compute, networking, identity, secrets, and service delivery\n\n - Develop progressive rollout, health-check, and rollback patterns for critical infrastructure\n\n - Build self-service platform capabilities, templates, and guardrails that shorten the path from code to production\n\n - Partner with research and product teams to remove delivery bottlenecks and turn recurring needs into reusable platform capabilities\n\n - Define practical observability standards across metrics, logs, dashboards, and alerting using tools such as Grafana\n\n - Define and own platform SLOs, partnering with service teams on targets, error budgets, and reliability priorities\n\n - Turn security and compliance requirements into reusable platform controls\n\n - Lead complex platform projects from technical design through adoption and steady-state operation\n   \n   \n\n\nWHAT WE’RE LOOKING FOR\n\n - 5+ years in infrastructure, platform, or security-focused engineering\n\n - Deep hands-on experience with Terraform or similar infrastructure-as-code tooling\n\n - Strong knowledge of cloud networking, IAM, secrets management, and CI/CD\n\n - Experience designing secure software delivery lifecycle environments from development through production\n\n - Production experience with Kubernetes or similar container orchestration platforms\n\n - Ability to debug across infrastructure layers and make sound trade-offs under ambiguity\n\n - Clear technical communication and a track record of leading cross-functional projects\n   \n   \n\n\nNICE TO HAVE\n\n - Experience operating ML/LLM training or inference infrastructure\n\n - Exposure to GPU infrastructure and distributed systems\n\n - Experience with zero-trust access patterns\n\n - Experience supporting compliance or audit-readiness programs\n\n\n\n\nWHAT WE OFFER\n\n - Cash compensation $150K–$300K with significant equity\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n\n\n\nGROWTH OPPORTUNITY\n\nYou’ll have direct influence over the platform behind open frontier AI research and products used by ambitious AI teams. Your impact will show up in faster delivery, safer operations, and less infrastructure work repeated across teams. We value ownership, technical judgment, and engineers who turn complex problems into simple, durable systems."}],"apiVersion":"1"}