Head of Compute

Applied Compute•San Francisco, CA

2d•Onsite

About The Position

The role At Applied Compute, securing the right compute on the right terms is what makes our post-training and agent infrastructure possible. As Head of Compute Partnerships, you'll own the sourcing, economics, and strategic positioning of the GPU capacity that powers everything we train, serve, and deploy for enterprise customers. This is one of the highest-leverage roles at the company. Compute is both our core input and our binding constrain. Your job is to make sure Applied Compute has a leading seat at the table structuring the commercial relationships that define our cost structure for years, getting early access to new hardware generations as they come online, and turning a fragmented global supply market into a durable advantage. You'll work directly with our founders, our GTM function, and the leadership teams at providers reshaping global compute, and you'll partner closely with our research and engineering teams to decide what we train, on what hardware, where, and at what cost.

Requirements

Strong business and financial instincts, with native fluency in unit economics, margin structure, and capital allocation, and the ability to model the long-term P&L consequences of complex supply decisions
Deep knowledge of the global AI compute market, including the providers, the hardware generations and their real tradeoffs, pricing dynamics, and where the market is heading over the next 12 to 24 months
A track record of negotiating and closing contracts at meaningful scale, finding and using leverage, and structuring deals that drive downstream economics
Comfort operating across finance, commercial, product, and engineering, and translating fluently between all of them
High ownership, with a habit of seeing gaps and building the fix before anyone asks

Nice To Haves

Experience structuring large infrastructure or capacity agreements
Existing senior relationships across hyperscalers, neoclouds, or regional compute providers
Background spanning both finance or capital allocation and hands-on commercial negotiation
Experience sourcing compute or hardware in a high-growth environment where supply was the primary constraint
An AI-native way of working, using LLMs, automation, and programmatic tools to move faster

Responsibilities

Own the unit economics of compute end-to-end, from the structure of individual contracts to the margin architecture across training and inference products to the long-term P&L consequences of today's supply commitments
Run global procurement of GPU capacity across hyperscalers, tier-one neoclouds, regional operators, and emerging providers
Negotiate and close reserved capacity agreements, spot and burst arrangements, MSAs, DPAs, and order forms
Secure early access to the latest accelerator generations in the quantities we need
Partner with finance and leadership on capital strategy: how much to commit, to whom, over what term, on which hardware, and with what balance sheet exposure
Build the frameworks that translate supply decisions into clear financial outcomes and let the company make large bets with conviction under uncertainty
Work with research to translate training roadmaps and RL workloads into concrete compute requirements, and feed back what's achievable
Partner with engineering on acceptance testing, goodput validation, and technical qualification of new providers and hardware