Forward Deployed AI Strategy Lead
Prime Intellect builds the 'Open Superintelligence Stack' — an integrated compute, training, inference, and sandbox platform that lets companies train, deploy, and continuously improve their own AI models and agents. It serves AI startups, 'neolabs', and enterprises (over 6,000 customers, including Ramp and Zapier) that want to own their model optimization loop rather than rely solely on closed frontier labs.
Maintainer signals as of 8/12/2026
Funding history
Investors
Projects
About Prime Intellect
Prime Intellect is a San Francisco-based AI infrastructure company building what it calls the Open Superintelligence Stack: a full-stack platform spanning GPU compute (on-demand and reserved clusters), large-scale reinforcement learning training ('Lab'), an Environments Hub with 2,500+ community RL environments, hosted evaluations, sandboxed code execution, and dedicated/serverless model inference with native LoRA support. The company maintains open-source libraries (verifiers and prime-rl) used to build and train RL environments, and publishes frontier open research such as the INTELLECT and SYNTHETIC model/dataset series. Prime Intellect works with AI startups, enterprises, and 'neolab' customers such as Ramp and Zapier, helping them turn production traces and evaluations into custom-trained, post-trained agent models that outperform closed frontier models on specific workflows at lower cost and latency. The company has raised over $150M in total funding, including a $130M Series A led by Radical Ventures with participation from NVIDIA Ventures, Intel Capital, and Dell Technologies Capital, and reports over $100M in annualized revenue.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead strategic customer deployments from technical discovery through proofs of concept, production deployment, expansion, and case studies. You will identify valuable AI workflows, translate them into evaluations and post-training opportunities, define executable scopes, coordinate with applied research and engineering, and drive customers through qualification, legal, procurement, deployment, and revenue expansion.
Requirements
- Strong intuition for AI products and workflows
- Ability to understand technical systems
- Excellent written and verbal communication
- Comfort working with executives, researchers, engineers, and operators
- High agency
- Ability to run multiple complex customer workstreams
- Strong commercial instincts
- Knowledge of post-training, agents, evaluations, reinforcement learning, and AI infrastructure
Responsibilities
- Lead strategic customer workstreams from technical discovery through deployment and expansion
- Identify high-value AI workflows
- Translate workflows into evaluations and post-training opportunities
- Define use cases, success metrics, evaluation designs, environment requirements, integrations, milestones, commercial structures, risks, and expansion paths
- Turn messy customer information into executable scopes
- Bring customer signals into research and product roadmaps
- Build discovery templates, qualification frameworks, proof-of-concept structures, proposals, pricing inputs, reference architectures, case studies, and deployment playbooks
- Move customers through qualification, legal, scoping, proposal, procurement, proof of concept, deployment, and expansion
Benefits
- Meaningful equity
- Flexible work in San Francisco or hybrid-remote
- Visa sponsorship
- Relocation support
- Professional development budget
- Team off-sites
- Conference attendance
- Direct exposure to frontier AI labs, leading AI startups, and enterprise AI teams
