Own Your Intelligence
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.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
Your Role
Compute is the scarcest input in AI, and the companies that secure it on the right terms will define the next decade. But the labs and enterprises we work with are not buying GPU hours. They are buying the ability to execute an AI roadmap: train the next model, post-train it on their own data, serve it in production, and do it again. Selling to them means understanding that roadmap and structuring a multi-year commitment around it.
As a Strategic Account Executive, you will own strategic customer acquisition and expansion for Prime Intellect's GPU infrastructure and Model Factory platform. You will build and close a portfolio of AI-native and enterprise accounts, working with CTOs, Heads of AI/ML, infrastructure leaders, and economic buyers to translate their training, post-training, and inference plans into committed capacity. You will construct deals around spend, term, workload expansion, and platform adoption — not feature checklists — and then grow every landed customer from compute into the full training stack.
You will work alongside our Solutions Architects on discovery, benchmarks, and POCs, and directly with leadership on the commercial structures that define how this category gets sold. The deals you close will shape what Prime Intellect commits to, builds, and becomes.
Responsibilities
Strategic Acquisition
Build and close a portfolio of strategic AI-native and enterprise accounts
Develop relationships with CTOs, Heads of AI/ML, infrastructure leaders, and economic buyers
Translate customers' training, post-training, and inference roadmaps into multi-year GPU capacity commitments
Partner with Solutions Architects on technical discovery, benchmarks, and POCs so every deal is won on proof
Deal Construction & Expansion
Build commercial proposals around committed spend, term length, workload expansion, and Model Factory adoption
Negotiate and close seven- and eight-figure agreements with economics that work for both sides
Expand landed compute customers into Model Factory, post-training, inference, and additional capacity
Partner with Compute and Finance on supply, pricing, and margin so what you sell is what we can deliver
Pipeline Discipline
Maintain rigorous qualification, forecasting, and next-step discipline across the portfolio
Report pipeline, forecast, and deal status to leadership with accuracy you stand behind
Feed market, competitive, and customer signal back into product, pricing, and compute strategy
What We're Looking For
Proven success selling highly technical infrastructure: cloud, GPU compute, AI/ML platforms, or adjacent developer infrastructure
Experience closing seven-figure enterprise agreements; eight-figure strongly preferred
Credibility with technical executives and ML/infrastructure teams — you can hold the room with a Head of AI and an engineer at the same time
Ability to sell economics, architecture, and strategic partnership, not just software features
Strong deal construction and negotiation skills, including multi-year commitments and consumption-based structures
Comfort operating in an early-stage, high-accountability environment where you own the number
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
Bonus:
Experience selling GPU capacity, reserved compute, or AI training infrastructure specifically
Background at a GPU cloud, neocloud, hyperscaler AI organization, or AI platform company
Existing relationships with AI labs, AI-native startups, or enterprise AI leaders
Experience as an early sales hire who helped define the playbook, pricing, and segmentation
How We Measure Success
Committed contract value · Contract duration · New strategic customers · GPU capacity sold · Model Factory attach · Post-training and inference expansion · Forecast accuracy
Why This Role
You will sell one of the most consequential products in technology to the people building the next generation of AI, in a market where the commercial playbook is still being written. You will work directly with leadership on deal structures that define the category, develop a network across the labs and enterprises shaping the industry, and build a track record in AI infrastructure sales that is increasingly rare and valuable.
What We Offer
On-target earnings of $225–$300k++ and meaningful equity
Flexible work (remote or San Francisco), with travel to customers as needed
Visa sponsorship and relocation support
Professional development budget
Team off-sites and conferences
A front-row seat to building the infrastructure layer for open AI