Compute Partnerships Lead

Location: San Francisco / Remote

Employment Type: Full time

Department: Operations

Prime Intellect is building the open superintelligence stack - from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full RL post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts.

We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others.

We are looking for a Compute Partnerships Lead to architect and operate our global compute supply strategy.

This role sits at the intersection of infrastructure sourcing, research enablement, and customer deployment. You will secure and manage GPU capacity across cloud providers, data centers, hardware vendors, and strategic infrastructure partners — ensuring we can support both:

• Dedicated enterprise deployments

• Hosted training and RL workloads

• Internal frontier model research

This is an execution-heavy individual contributor role with significant strategic leverage. The expectation is not just signing agreements - but building durable, scalable capacity systems that directly power revenue and research velocity.

• Develop and execute Prime Intellect’s global GPU sourcing strategy across H100/H200/B200-class infrastructure and beyond.

• Structure commercial agreements that balance cost, flexibility, term length, and growth optionality.

• Identify and evaluate infrastructure partners across hyperscalers, specialized AI clouds, data centers, colocation providers, and hardware vendors.

• Lead negotiations on pricing, SLAs, capacity reservations, expansion rights, and risk allocation.

• Continuously optimize blended gross margins through disciplined sourcing and contract structuring.

• Secure capacity for internal frontier RL research and model training.

• Coordinate closely with research and engineering teams to understand workload requirements (training vs inference vs long-context deployments).

• Align capacity planning with enterprise deployment roadmaps.

• Ensure compute supply keeps pace with customer expansion and new model launches.

• Work with infrastructure, platform, and DevOps teams to ensure partner capacity is onboarded efficiently and runs reliably in production.

• Track uptime, delivery timelines, and performance metrics across partners.

• Manage escalation paths and issue resolution with providers.

• Design playbooks for expanding from pilot deployments to large-scale clusters.

• Monitor global GPU supply dynamics, pricing trends, export constraints, and vendor roadmaps.

• Diversify supply to reduce concentration risk.

• Model long-term capacity requirements across revenue scenarios.

• Identify opportunities for structured capacity (e.g., reserved blocks, hybrid models, co-investment structures).

• Build long-term strategic relationships with infrastructure providers.

• Explore novel partnership models that create competitive advantage.

• Support cross-functional collaboration between Finance, Research, Sales, and Operations.

• Provide infrastructure insights for board and investor conversations.

• 3–7+ years in infrastructure partnerships, business development, commercial sourcing, or AI infrastructure strategy.

• Direct experience negotiating GPU/cloud/data center agreements strongly preferred.

• Strong understanding of AI workloads (training vs inference, memory constraints, networking, utilization economics).

• Experience working cross-functionally with engineering and finance.

• High commercial discipline — comfortable modeling margin, utilization, and contract tradeoffs.

• Comfortable operating in constrained supply environments.

• Strong ownership mentality — you build systems, not just deals.

• Ability to travel and manage global partnerships across time zones.

• Competitive Compensation + equity incentives

• Flexible Work (remote or San Francisco)

• Visa Sponsorship and relocation support

• Professional Development budget

• Team off-sites and conference attendance

• Opportunity to shape decentralized AI at Prime Intellect