AI Engineer (Deployed)
New York City / San Francisco - Onsite
$200k - $400k + significant equity
We're working with one of the most talked-about labs in AI. Multi-billion dollar valuation, backed by the biggest names in tech, and building frontier models that sit at the edge of what's currently possible. They're now taking that research into the enterprise, and this team is how it happens.
As a Forward Deployed Engineer, you own agentic systems end to end, from the first customer conversation through to something running in production at scale. You'll be deep in the model layer, building agents that handle real workloads inside some of the largest companies in the world. You'll also be in the room with those customers, which is what makes this role rare: frontier research on one side, hard commercial problems on the other, and you standing between them.
What you'll do:
- Ship agents that hold up in production, built on models most engineers won't touch for another year.
- Sit with customers, work out what they actually need, and design the system that gets them there.
- Take what you learn on the ground and turn it into fine-tuned models and better research direction.
- Deploy into whatever environment the customer runs, including locked-down and on-premise setups.
- Write the playbook for a team that doesn't have one yet.
What we're looking for:
- 5+ years building and shipping production software, ideally where AI was central rather than bolted on. Shorter track records considered if the trajectory is exceptional.
- Strong fundamentals in Python and/or TypeScript, with real systems running behind you.
- Hands-on depth across the modern AI stack: agents, orchestration, retrieval, evals, fine-tuning.
- Experience deploying enterprise software in cloud or hybrid environments, with the DevOps chops to match.
- Credible in front of customers. You can hold a technical conversation and a commercial one in the same meeting.
- High agency, high ownership, comfortable when nothing is defined yet.
The people who do well here tend to come from frontier labs, elite deployment-heavy engineering teams, or the technical arms of top-tier advisory firms. A strong CS or engineering education, ideally from a leading program, is expected.