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Founding Engineer | AI-Native Ops Infrastructure at Legion Health. Remote Location: San Francisco. About Legion Health. Legion Health (YC S21) is building the . AI-native operations layer for psychiatric care. .. We run our own psychiatric practice and are rebuilding what happens . outside. the visit—scheduling, intake, documentation, billing, risk detection, and coordination. Not “doctor-in-a-box,” but the operational backend that mental health actually runs on.. Our agent infrastructure already supports . 2,000+ patients with one human support lead. . The systems you build will land in real clinical workflows immediately.. Role: Founding Engineer – AI-Native Ops Infrastructure (In-Person SF). Hey—I’m Daniel, co-founder & CTO. I’m hiring a . Founding Engineer. to own core backend + agent systems end-to-end.. You’ll help design and build the infrastructure that coordinates human clinicians, support staff, and AI agents like a single, coherent system.. Roles evolve quickly here—including mine. I’m looking for someone who wants to . grow into owning major parts of the system. , not someone depending on me to stay in a narrow CTO role forever.. What you’ll do. Own our event-driven backend. – Architect and scale our Node.js / TypeScript / Supabase (Postgres) / AWS stack. Design schemas, invariants, and workflows that encode how psychiatric care actually operates. Turn messy real-world processes into clean state machines and event streams.. Build real LLM agents as coworkers. – Implement tool use, retries, memory, and safety rails. Design action schemas and evaluation loops so agents can run reliably in production. Work on orchestration, context management, and multi-step workflows.. Shape human + AI ops UX. – Build internal tools used by both humans and agents. Make it trivial to see “what happened, why, and what should happen next” in any patient journey.. Define world-state & simulation. – Model the canonical state of a patient’s journey across time. Power alerting, routing, and decision-making from that live simulation.. Own data, safety & compliance. – Engineer HIPAA-compliant pipelines for transcripts, events, and EHR data. Ensure PHI access, agent actions, and human overrides are all auditable.. Drive architecture & strategy. – Work directly with me to debate tradeoffs, define new primitives, and decide what we build next.. You don’t need to be a pure backend engineer—we value. great product engineers who can learn fast. , make strong simplifying decisions, and grow into owning backend/agent systems.. You might be a fit if…. You’ve . owned real systems 0→1 or 1→N. , not just tickets.. You think in . events, state, and invariants. , not just CRUD endpoints.. You’re either already . LLM-fluent. or a strong systems/backend engineer who can get dangerous fast.. You care about velocity . and. correctness—moving quickly while keeping things understandable and robust.. You like small, high-candor teams and direct feedback.. You want to see your work go live in production . weekly. , not sit on a roadmap.. Nice to have (but not required). Experience with Node.js / TypeScript, Postgres, or Supabase.. Experience with LLMs, agents, tool-calling, or RAG.. Experience in healthcare, fintech, or other regulated / high-stakes domains.. Experience in early-stage startups or founding teams.. Our stack. Backend: Node.js, TypeScript, Supabase (Postgres), AWS (ECS, Lambda, S3). Frontend: Next.js 15 (App Router), Tailwind, Vercel. AI: OpenAI, Anthropic, tool-calling agents, embeddings + vector DBs, Langfuse-style observability. Other: PHI security, audit trails, real-time schedulers, transcript ingestion. Interview process. Intro call (20–30 min) with Daniel – background, what you’ve built, what you want.. Systems / portfolio deep dive (45–60 min) – walk through 1–2 systems you’ve shipped; architecture, tradeoffs, failure modes.. Practical work trial (1–2 hours async) – short, realistic backend/LLM-systems exercise. No leetcode, no puzzles.. Final onsite (1–2 hours) – meet the team, pair on a real issue, and talk through how you’d own a domain.. We aim to go from first conversation to offer in . 7–10 days. .. Compensation. Salary: . $130,000–$180,000. (depending on experience). Equity: . 0.2%–0.8%. meaningful early ownership. In-person in San Francisco