Member of Technical Staff - Datacenter Operations

Prime Intellect; San Francisco (CA); On-site; USD 150,000 - 300,000; Full time

Job summary

Prime Intellect in San Francisco is building the open superintelligence stack and seeks an experienced infrastructure professional to own the operational readiness of our GPU cloud hardware.

You will coordinate deployments, manage datacenter partnerships, and lead incident response, ensuring reliable production capacity for frontier-scale workloads. The role demands hands-on experience with rack-mounted servers, networking, and high-density cooling in a fast-moving environment.

Qualifications

• 3+ years in datacenter operations or production systems.
• Hands-on experience deploying rack-mounted servers and networking gear.
• Experience coordinating datacenter providers and vendors.
• Knowledge of Linux diagnostics, BMC consoles, and health tools.
• Strong ownership and documentation habits.

Responsibilities

• Coordinate rack deployment, cabling, inventory, and testing with partners and engineering.
• Maintain asset records, rack layouts, power allocations, and spare parts.
• Lead hardware fault triage, remote hands, and RMA workflows.
• Establish maintenance plans and procedures minimizing disruption.
• Track capacity readiness, repair times, and operational risks; automate reports.
• Partner with facilities on power, cooling, monitoring for high-density GPUs.
• Create runbooks and escalation procedures for incident response.

Skills

GPU servers

Rack deployment

Power budgeting

Cabling

Automation scripting

Job description

Own Your Intelligence

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.

Role Impact

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.

Core Technical Responsibilities

• 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

Required Experience

• 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

Infrastructure Skills

• 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

Nice to Have

• 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

Growth Opportunity

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.

Compensation

Cash compensation range of $150,000–$300,000 plus equity incentives.