Head of Compute

Prime Intellect; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive cash compensation

Meaningful equity

Flexible work (remote or SF)

Visa sponsorship & relocation support

Team off-sites

Job summary

Prime Intellect is building the open frontier AI infrastructure stack, unifying compute, environments, evaluations, and secure sandboxes for post-training at frontier scale. The role focuses on owning compute economics, sourcing, contracting, and shaping strategic compute partnerships to enable open models and major open ecosystem bets.

You will work with leadership and researchers to translate training roadmaps into concrete compute requirements, while negotiating capacity with providers to

Qualifications

• Strong business and financial instincts with focus on unit economics and capital allocation.
• Ability to model long-term P&L consequences of supply decisions.
• Experience negotiating and structuring large-scale contracts.

Responsibilities

• Own end-to-end compute economics: unit economics, margin architecture across training and inference products.
• Partner with Finance and leadership on capital strategy and exposure.
• Build frameworks turning supply decisions into clear financial outcomes for multi-hundred-million-dollar bets.

Skills

Unit economics

Financial modeling

Negotiation

Strategic thinking

Cross-functional collaboration

Tools

Financial systems

Market analysis tools

Job description

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.

Your Role

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.

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.

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.

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.

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.

Responsibilities

Compute Strategy & Economics

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

Sourcing & Contracting

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

Co-Design with Research & Engineering

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

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 — 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

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

What We're Looking For

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

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

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

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

Comfortable operating at the intersection of finance, commercial, product, and engineering — and translating fluently between all of them

High ownership: you see gaps and build the fix before anyone asks

AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster

What We Offer

Competitive Cash Compensation + meaningful equity

Flexible work (remote or San Francisco)

Visa sponsorship and relocation support

Team off-sites and conferences

A front-row seat to building the infrastructure layer for open AI