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About the Role

As a Forward Deployed AI Strategy Lead, you will work directly with strategic customers to identify high-value AI workflows, translate them into evals and post-training opportunities, scope technical deployments with Applied Research, and turn early experiments into long-term revenue. You are part customer owner, part product strategist, part AI systems thinker, and part commercial operator. You will sit with both sides and help invent the answer.

Responsibilities

Lead high-priority customer workstreams from first technical discovery through POC, deployment, expansion, and case study.
Work with customers building agents, automating complex workflows, improving model performance, reducing inference cost, building domain-specific evals, or running frontier-scale post-training.
Help customers define what to train or evaluate, what success means, which workflows are worth turning into environments, what data or traces are needed, what should be automated, supervised, or measured, which model should be adapted, and the path from prototype to production.
Take messy customer conversations, artifacts, docs, goals, and constraints and turn them into crisp scopes for Applied Research and Engineering.
Define use cases, success metrics, eval design, environment requirements, integration needs, milestones, commercial structure, risks and dependencies, and expansion path.
Bring customer signal into the research and product roadmap, helping the team identify which evals, environments, agents, and post-training recipes matter most.
Prioritize work that advances the frontier and unlocks meaningful customer outcomes.
Help answer questions about converting real-world workflows into RL environments, useful evals, sufficient verifiers, trainable tasks, managed RL vs. prompting, and proving performance improvement.
Build the operating system for Prime Intellect’s applied AI motion, including discovery templates, customer qualification frameworks, POC structures, proposal language, pricing and packaging inputs, reference architectures, case studies, technical narratives, and deployment playbooks.
Turn one-off customer wins into a repeatable category.
Work with leadership to move customers through qualification, legal, scoping, proposal, procurement, POC, deployment, and expansion.
Own senior customer relationships, create urgency, write crisp follow-ups, navigate internal and external stakeholders, and ensure deals do not die in ambiguity.

Requirements

Unusually strong across technical understanding, customer empathy, product judgment, and execution.
Experience in forward deployed engineering or technical GTM.
Experience in AI product strategy or applied AI.
Experience in solutions architecture for highly technical products.
Experience in early-stage startup operating roles.
Experience in product management for AI, infra, devtools, or enterprise software.
Experience in ML engineering, applied research, or AI engineering with customer exposure.
Experience in venture/investing roles with deep technical and commercial work in AI.
Strong intuition for AI products and workflows.
Ability to understand technical systems without needing every detail pre-digested.
Excellent written and verbal communication.
Comfort operating with executives, researchers, engineers, and operators.
High agency and low ego.
Ability to run multiple complex customer workstreams.
Taste for what makes a deployment valuable.
Strong commercial instincts.
Deep curiosity about post-training, agents, evals, RL, and AI infrastructure.
Ability to make progress before the playbook exists.

Skills

RL
SFT
evals
agents
MCP
LangGraph
DSPy
Stagehand
Browserbase
tool-use workflows
enterprise AI teams
frontier AI companies
reading traces
reading product docs
reading API docs
reading technical specs
writing proposals
writing customer memos
writing technical scopes
writing launch narratives
founder experience
early startup experience
strong network across AI startups
strong network across research labs
strong network across enterprise software buyers

Location

San Francisco
hybrid-remote

Work Type

hybrid-remote

Experience Level

Forward deployed engineering
Technical GTM
AI product strategy
Applied AI
Solutions architecture
Early-stage startup operating
Product management
ML engineering
Applied research
AI engineering
Venture/investing

Benefits

Competitive cash compensation
Meaningful equity
Professional development budget
Team off-sites
Conference attendance
Direct exposure to frontier AI labs, leading AI startups, and enterprise AI teams
Visa sponsorship
Relocation support

About the Company

Prime Intellect is building the infrastructure that frontier AI labs build internally, and making it available to everyone.
Our platform, Lab, brings together environments, evaluations, sandboxes, verifiers, training, inference, and deployment into one full-stack system for post-training.
We help customers move beyond prompting and static benchmarks toward models and agents that improve against their own tools, workflows, and feedback loops.
We train open state-of-the-art models on the same stack we give customers, and we work with some of the most ambitious AI companies, enterprises, and research teams in the world.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and leading founders and executives from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, LangChain, Browserbase, Cloudflare, Sierra, Databricks, and more.
We are building the open superintelligence infrastructure stack — and we need people who can bring it into the real world.