AI Engineer

ABOUT THE JOBWe’re removing one of the last great barriers to progress in the physical world.While software moves fast, industries like aerospace, healthcare, and energy are still slowed by outdated, manual systems.We are on track to raise our Series A, backed by a 14× oversubscribed $4.5m seed round from Tier-1 VCs such as Coinbase, Reddit, Klarna, and Spotify. Our world-class team includes former unicorn founding engineers and talent from X, Google, Amazon, and Yandex. We value people who want to win and thrive in high-ownership environments.We’re building the system that lets complex, real-world work move at software speed.WHO WE ARE LOOKING FORWe're looking for an Applied AI Engineer who thinks in user workflows and model behavior, not benchmarks or isolated prompts.This is a role for someone who wants to decide what AI should do, build it end-to-end, and put it in users' hands.You will fit right in if you have experience with:Applied AI — Design and build LLM-powered features that solve real workflows, from prompt to productionModel Behavior — Reason about why models fail, when to use which model, and how to make them reliable in productionEvals & Iteration — Build evals that actually catch regressions and drive improvements, not vanity metricsAgents & Tooling — Design multi-step agents, tool use, and orchestration for complex domain workflowsDocument Intelligence — Extract structured data from messy real-world documents (PDFs, scans, forms, tables)Product Judgment — Be opinionated about what AI should do, what it shouldn't, and when "good enough" shipsWHAT YOU WILL DOShip from Day 1 — Deploy AI features to production immediately and own a real user-facing surface areaOwn it end-to-end — From problem definition to prompts, evals, monitoring, and iterationSolve real problems — Sit in customer calls, look at real documents, debug bad outputs, and make the system betterWHAT WE ARE LOOKING FOR TECHNICALLYStrong experience with Python and modern LLM tooling (OpenAI/Anthropic/Azure OpenAI SDKs, structured outputs, function calling)Experience building production AI systems beyond a wrapper around a chat APIComfortable with evals, prompt engineering, and reasoning about model failure modesAbility to work across the stack to integrate AI into real product workflows (TypeScript/React frontend, Python backend)Ability to reason about complex domain workflows, not just prompt-responseStrong plus if you have:Founder or ex-founder experienceEarly-stage or stealth startup backgroundFounder fellowships or similar environments (EF, YC, Antler, etc.)Experience building AI-powered products in productionExperience working where requirements were unclear and evolving