Compute Finance and Strategy

Building Open Superintelligence InfrastructurePrime 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, Tri Dao, Dylan Patel, Clem Delangue, Emad Mostaque, and many others.Your RoleCompute is the foundational input of the AI era. The companies, models, and capabilities that define the next decade will be shaped by who has access to compute, on what terms, at what economics, and how it gets allocated across the systems that get built on top of it. The financial and operational architecture for an asset class of this consequence is still being built, and the playbooks for navigating it don't yet exist. The people who write them will define how the AI infrastructure industry develops over the next decade.You will own the analytical foundation for how we understand global compute markets: pricing supply across regions and term lengths, modeling the economics of large GPU commitments, evaluating neoclouds and hyperscalers, and turning that work into provider decisions, commercial structures, and customer-facing products.The work sits at the intersection of infrastructure, finance, and AI systems. You will evaluate questions like when an H200 cluster is the right fit versus GB200 or GB300, how networking and storage constraints affect real workload performance, how utilization assumptions change the economics of a multi-year commitment, and how regional power, colo, and capital costs flow through to GPU-hour pricing. You will diligence providers not just on headline price, but on delivery timeline, cluster architecture, reliability, support model, contractual risk, and ability to serve frontier AI workloads.The decisions you support will directly shape Prime Intellect’s ability to deliver high-quality compute to researchers, AI labs, and enterprises building on top of our stack.ResponsibilitiesCompute EconomicsBuild and own the financial models that price our compute supply: per-cluster economics, contract structures, hardware generation comparisons, geographic and provider differentialsModel the economics of every meaningful supply decision — reserved vs. spot tradeoffs, term length, commitment level, hardware generation, provider mix, geographyOwn margin architecture: margin by workload, customer, product, and contract, so we always know what's actually profitable and where the leverage isModel the long-term P&L consequences of today's supply bets under multiple demand and pricing scenariosStrategic Bets & Capital AllocationPartner with leadership on the biggest decisions the company makes: which providers to commit to, which hardware generations, what geographies to lean into, how aggressively to scaleBuild the financial frameworks that turn ambiguous strategic questions into decisions we can make with convictionOwn the long-range plan, scenario models, and capital allocation framework across compute, headcount, and product investmentProvider Engagement & DiligenceEngage directly with neoclouds, hyperscalers, and emerging providers on economic and technical diligenceRun the financial side of supply qualification — what we accept, what we reject, what we negotiate harder onTranslate technical performance characteristics into commercial recommendationsBuild the repeatable analytical process for evaluating new entrants to the global supply marketMarket IntelligenceTrack pricing, availability, and provider dynamics continuously across every major marketBuild Prime Intellect's view of the global compute market — who's credible, who's mispriced, where supply is tightening, where the next wave of capacity is coming onlineDevelop the analytical basis for our market positioning: when to commit hard, when to hold flexibility, where to lean in geographicallyCross-functional PartnershipPartner with Strategic Finance on how compute economics flow through to the company P&LPartner with Engineering on the technical performance characteristics that drive cluster economicsPartner with Sales and Product on pricing strategy for consumption-based and hybrid productsBuild board-ready analyses on supply strategy, capital allocation, and market positioningWhat We're Looking For4–7+ years in roles that combine financial rigor with real-world strategic or operational engagement. Backgrounds we'd find compelling include:Investment banking, private equity, or growth equity with exposure to infrastructure, cloud, semiconductors, or technologyQuantitative or strategist roles at hedge funds, commodities desks, or trading firmsInfrastructure investing, project finance, or structured creditStrategic finance or BizOps at a high-growth cloud, AI infrastructure, or compute-intensive companyExceptional modeling and analytical skills — you build the models yourself, and your models reflect how the business actually worksGenuine technical curiosity. You don't need deep technical background to start, but you should be excited to develop fluency in GPU architectures, networking, cluster performance, and what makes one piece of compute economically different from anotherStrong commercial and strategic judgment — you understand that finance's job is to drive better decisions, not produce more analysisComfortable engaging directly with vendors, partners, and senior counterparts at provider companiesAbility to operate across registers — building rigorous models, briefing leadership on strategic implications, and running diligence with senior counterparts at provider companiesHigh ownership — you see gaps and build the fix before anyone asksAI-native in how you work: you use LLMs, automation, and programmatic tools to move fasterBonus:Direct experience modeling datacenter, colocation, cloud, or power/energy economicsBackground covering AI infrastructure, cloud providers, semiconductors, or compute marketplaces from the banking, investing, or trading sideHands-on experience with cluster benchmarking, training/inference workload economics, or compute marketplacesWhy This RoleCompute economics is becoming one of the most consequential domains in technology, and almost no one is approaching it with the rigor it deserves. You'll be in the room for the decisions shaping Prime Intellect's future and, in real ways, the future of open AI infrastructure. You'll work directly with leadership on the calls that define the company, develop deep expertise in a market most finance professionals only read about, and build a foundation in compute economics that is increasingly valuable across the industry.What we offerCash Compensation Range of $200-300k + meaningful equityFlexible work (remote or San Francisco)Visa sponsorship and relocation supportProfessional development budgetTeam off-sites and conferencesA front-row seat to building the infrastructure layer for open AI