Applied AI: Product Strategy & Revenue Lead

About the role

This is not a traditional sales role. It is not a traditional product role. It is not a traditional solutions engineering role. You will help define how Prime Intellect turns frontier post-training infrastructure into a product customers can understand, buy, deploy, and expand.

Responsibilities

• Work with frontier AI labs, fast-growing AI startups, and enterprise AI teams to understand what they are trying to build, where their current stack breaks, and how Prime Intellect can become the infrastructure layer underneath their post-training and agent workflows.
• Turn vague, high-stakes customer conversations into clear technical and commercial strategy: What is the customer actually trying to improve? Is the wedge compute, evals, environments, sandboxes, managed RL, SFT, inference, or a full-stack workflow?
• Help Applied Research build or prototype what should be in scope for a POC versus a long-term deployment.
• Identify patterns across customer conversations, build repeatable narratives, define packaging, sharpen use cases, and help the team understand which customer asks are one-off noise versus signs of a massive market.
• Own high-value customer opportunities from first serious conversation through qualification, scoping, proposal, POC, procurement, and expansion.
• Create momentum through ambiguity and turn early deployments into expansion and long-term platform revenue.
• Work extremely closely with Applied Research to prioritize customer-facing work by bringing signal from the field: Which evals matter? Which environments should we build? Which agents or workflows are most commercially valuable?

Qualifications

• Strong product and commercial judgment.
• Ability to understand technical products quickly.
• Excellent written communication.
• High agency and comfort with ambiguity.
• Taste for what makes a customer problem real.
• Sharp instincts around enterprise buying, POCs, procurement, and expansion.
• Obsession with AI, post-training, agents, evals, and infrastructure.
• Ability to create structure where none exists.

Skills

• Technical taste to understand where an RL/post-training workflow is real, where a customer is hand-waving, and where a sharp Applied Research prototype could unlock a major deal.
• Strong network across AI startups, research labs, or enterprise AI teams.
• Founder mentality and willingness to do unglamorous work to win.

Benefits

• Competitive cash compensation and meaningful equity.
• Flexible work in San Francisco or hybrid-remote.
• Visa sponsorship and relocation support.
• Professional development budget.
• Team off-sites and conference attendance.
• A front-row seat to building the infrastructure layer for open AI.

Pay

Competitive cash compensation and meaningful equity.

Schedule

Fully remote or San Francisco office.