Founding Engineer | AI-Native Ops Infrastructure

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

1. Intro call (20–30 min) with Daniel – background, what you’ve built, what you want.

2. Systems / portfolio deep dive (45–60 min) – walk through 1–2 systems you’ve shipped; architecture, tradeoffs, failure modes.

3. Practical work trial (1–2 hours async) – short, realistic backend/LLM-systems exercise. No leetcode, no puzzles.

4. 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