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Head of Compute

Prime Intellect· Compute / Finance
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San FranciscoFull-timePosted 6mo ago

About the role

Prime Intellect is building an open superintelligence stack and is seeking a Head of Compute to own the sourcing, economics, contracting, and strategic positioning of GPU supply that powers training, serving, and selling of open frontier AI. The role collaborates with research, engineering, and leadership to shape compute strategy, procurement, and market positioning for a multi-year, high-impact construct in a rapidly evolving global AI compute market.

Responsibilities

  • 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
  • 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
  • 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
  • Shape the commercial architecture of the open compute ecosystem: how committed capacity, spot markets, credit structures, and partner economics fit together
  • 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
  • Negotiate and close reserved capacity agreements, spot and burst arrangements, MSAs, DPAs, and order forms at nine- and ten-figure scale
  • Secure early access to the latest generations of accelerators (B200, GB200, and what comes next) — in the quantities we need, before our competitors
  • Build and maintain the senior relationships that make Prime Intellect the partner of choice for providers deciding where to allocate scarce capacity
  • Work closely with our research team to translate training roadmaps, RL workloads, and open model ambitions into concrete compute requirements
  • Partner with Engineering on acceptance testing, goodput validation, and the technical qualification of new providers and hardware
  • 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
  • Track pricing, availability, and provider dynamics continuously across every major global market
  • Serve as the internal source of truth on the compute market — credible, well-priced, and forecasting supply dynamics
  • Advise leadership on strategic bets that define the company: accelerators, providers, geographies, contract structures, and timing

Qualifications

  • Strong business and financial instincts — unit economics, margin structure, and capital allocation with long-term P&L modeling
  • Deep fluency in the global AI compute market: providers, hardware generations, pricing dynamics, and near-term market trends
  • Technical enough to read vendor specs and discuss workloads with researchers
  • Serious commercial experience: negotiate and close contracts at meaningful scale and understand how deal structure drives downstream economics
  • Comfort operating at the intersection of finance, commercial, product, and engineering and translating between them
  • High ownership and proactive problem-solving
  • AI-native in approach: use LLMs, automation, and programmatic tools to move faster

Skills

Required:Compute economicsProcurement & contractingMarket intelligenceVendor negotiationsTechnical collaboration

Benefits

  • Competitive Cash Compensation + meaningful equity
  • Flexible work (remote or San Francisco)
  • Visa sponsorship and relocation support
  • Professional development budget
  • Team off-sites and conferences
  • Front-row seat to building infrastructure for open AI
Last updated Jul 15, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
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