About FleetAI
FleetAI works with frontier labs, hyperscalers, and enterprises to help develop and deploy the next generation of embodied agents. We see the creation of evals and environments, codifying human goals for agents, as the highest leverage activity in the buildup to ASI.
Backed by Sequoia Capital, Menlo Ventures, and SV Angel, we're growing fast and building the core infrastructure to unlock the next generation of agents.
The Opportunity
FleetAI is looking for a Member of Technical Staff to own our real world and synthetic data pipelines and collaborate closely with our team and frontier research labs to develop realistic scenarios and simulations for agents. This role is for someone who moves fast, thinks in days not months, and isn't afraid to do a bit of everything across the stack. If you're energized by ambiguity, thrive at the frontier of AI development, and know how to get the most out of AI agents, this is the role for you.
What You'll Do
- Own and scale real world and synthetic data pipelines end to end.
- Collaborate directly with frontier research labs to design and develop realistic agent environments and simulations.
- Delegate and manage fleets of coding agents in parallel to accelerate development.
- Work across the full tech stack, engineering and non-engineering alike, to do whatever it takes to move the business forward.
- Ship fast, with precision, without cutting corners. Cut scope instead.
You Should Have
- Deep technical expertise in at least one of: AI research, low-level infrastructure, or AI agent engineering.
- A proven ability to move extremely fast while maintaining quality and attention to detail.
- Strong experience working with and directing AI agents. You think in terms of delegation, not just execution.
- High agency and comfort operating in ambiguity. You know what to do when left to your own devices.
- The ability to context switch quickly across tasks and priorities without losing the thread.
Nice to Have
- Background as a founder or early engineer at an early-stage startup.
- Experience in AI research or post-training workflows.
- Familiarity with agent evaluation, safety research, or simulation environments.
