Forward Deployed AI Strategy Lead
Prime Intellect provides an open superintelligence stack for training, evaluating, deploying, and continuously improving AI agents and models. Its platform combines RL environments, hosted training, inference, GPU compute, secure sandboxes, and open-source research tooling for researchers, startups, and enterprises.
Maintainer signals as of 8/23/2026
Funding history
Projects
About Prime Intellect, Inc.
Prime Intellect operates an integrated AI infrastructure platform spanning Lab, hosted reinforcement-learning training, evaluations, environments, inference, secure sandboxes, and on-demand or reserved GPU compute. It also develops open-source tools including Verifiers, prime-rl, and Prime Agent, supporting workflows from environment creation and model evaluation through post-training and production deployment. The company serves researchers, startups, enterprises, and teams building agentic AI systems, with customer examples including Ramp and Zapier.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Prime Intellect is seeking a Forward Deployed AI Strategy Lead to work directly with strategic customers, identify high-value AI workflows, translate them into evaluations and post-training opportunities, scope technical deployments with Applied Research, and turn experiments into long-term revenue.
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 and low ego.
- Ability to run multiple complex customer workstreams.
- Strong commercial instincts.
- Deep curiosity about post-training, agents, evaluations, reinforcement learning, and AI infrastructure.
Responsibilities
- Lead strategic customer workstreams from technical discovery through proofs of concept, deployment, expansion, and case studies.
- Identify high-value AI workflows and translate them into evaluations and post-training opportunities.
- Define use cases, success metrics, evaluation designs, environment requirements, integrations, milestones, commercial structures, risks, dependencies, and expansion paths.
- Turn ambiguous customer information into executable scopes for Applied Research and Engineering.
- 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
