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San Francisco, California, United States
Onsite
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
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.
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.
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.
Coordinate rack deployment, cabling, inventory, and acceptance testing for new GPU capacity with datacenter partners and engineering teams
Maintain accurate asset records, rack layouts, power allocations, cabling documentation, and spare-parts inventories
Lead hardware fault triage and coordinate remote hands, vendor escalations, component replacement, and RMA workflows
Establish maintenance plans and change procedures that minimize customer disruption and protect equipment and data
Track capacity readiness, hardware failure trends, repair times, and operational risks; automate repetitive reporting and workflows
Partner with facility teams on power, cooling, environmental monitoring, and readiness for high-density GPU deployments
Create runbooks and escalation procedures and support incident response across datacenter and infrastructure teams
3+ years in datacenter operations, hardware infrastructure, or production systems operations
Hands-on experience deploying and troubleshooting rack-mounted servers, networking equipment, and structured cabling
Experience coordinating datacenter providers, remote hands, and hardware vendors through deployments and incidents
Working knowledge of Linux diagnostics, BMC consoles, and server hardware health tools
Strong operational judgment, documentation habits, and ownership of issues through resolution
GPU server components, PCIe devices, memory, storage, and hardware diagnostics
Rack power budgeting, redundant power paths, airflow, and high-density cooling fundamentals
Fiber and copper cabling, optics, labeling, and physical network troubleshooting
Asset tracking, spares management, change control, and incident management
Basic scripting for inventory, health checks, and operational automation; familiarity with safe datacenter working practices
Experience with NVIDIA DGX/HGX systems or large GPU cluster deployments
Liquid-cooled infrastructure and coordination with facility engineering teams
Experience bringing up new datacenter sites or expanding multi-site capacity
Hardware qualification, burn-in testing, and reliability analysis
Experience integrating physical operations with automated fleet provisioning
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.
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.
Apply now and join us in our mission to democratize access to planetary scale computing.
Cash compensation range of $150,000–$300,000 plus equity incentives.