Open role · Product engineering

Full Stack AI Engineer

Own the stack. Close the loop.

We are hiring full stack AI engineers who own real work end to end, front end and back end, and keep messy real-world integrations alive in production.

Remote Full time Individual engagement
01

About Linear Health

We are an AI-native healthcare operations platform in the US. We sit above the electronic health record and automate the outbound work clinics do by hand today: referrals, prior authorization, scheduling, care gap closure, and patient outreach across voice, SMS, and email. Our customers are healthcare providers across the US, including federally qualified health centers serving patients who often have nowhere else to go. We are lean, profitable, and moving fast.

02

What you would build

  • Python and FastAPI backends on AWS (EKS, Kubernetes Jobs, SQS, DynamoDB, PostgreSQL, Bedrock, Secrets Manager)
  • Web front end in React: coordinator dashboards, admin surfaces, patient chatbot widgets
  • Browser automation with Playwright against payer portals and any system with no API, including logins, OTP, and bot detection
  • Document extraction and vision pipelines for referrals, faxes, and prior authorization packets, with confidence gating and human review on anything uncertain
  • EHR and legacy integrations: Athena REST APIs as our primary, AdvancedMD through Mirth Connect, NextGen, eClinicalWorks, HL7, FHIR, and the fragmented interfaces clinics actually run on
  • Voice AI touch points on our enterprise ElevenLabs stack
03

Who we are looking for

We have learned exactly what makes someone succeed here, so we screen for it on purpose.

You pick things up fast.

We explain a workflow once and you run with it. If you need it explained three times, or need to be walked through every step, this is not the seat.

You take full ownership.

You carry work all the way to done without being chased, you keep your files and your work where they belong, and you close your own loops. Nobody should have to chase you for basics.

You are proactive.

You spot gaps, ask the right questions early, and flag problems before they grow, instead of going quiet or waiting to be told.

You communicate.

Strong, clear written and spoken English, because you will be on live calls, in customer meetings, and writing customer-facing messages.

You take deadlines and reliability seriously.

You do not need US healthcare experience. You do need to ramp fast and be comfortable in a regulated, high-stakes domain.

04

Must have, and be ready to prove

  • Strong full stack. Real depth in Python and FastAPI, and real production web React, not only React Native or low-code tools
  • Hands-on Playwright and browser automation. This is core to the work, not a bonus
  • At least one AI system you built end to end: an agent, a document extraction pipeline, or similar
  • Hands-on AWS. You have deployed and debugged real workloads
  • Fluent, confident spoken and written English
Bonus

HL7, FHIR, Mirth Connect, Kubernetes, and any healthcare exposure. You do not need SOC 2 or HIPAA experience, but you should be aware of what they are

05

This is an individual engagement

You will do this work yourself. No agencies, no teams, no consultancies, no subcontracting, and no passing the work to anyone else. If you are an agency, or you plan to route this through other people, please do not apply.

We check for this throughout the engagement. If we find at any point that you misrepresented yourself, or that someone else is doing the work, the engagement ends immediately.

06

The engagement

  • Long-term and full-time. The first 90 days are a paid trial while we both confirm the fit. We invest heavily in the people who clear it
  • We cover the AI tooling you need to do the work, including your Claude licence
  • You must overlap at least 6 hours every working day with US Central Time. For most of the world that means working into your evening or night. Only apply if that genuinely fits your life
  • The work is intense and the bar is high. We move fast
  • Compensation is discussed directly with you early in the process
07

How we work

We are a small, flat, fast team and we hold a real bar. Apply only if this is the environment you want, or the one you are hungry to grow into.

  • We live on Slack all day. You are online, reachable, and quick to respond during working hours
  • Daily standup is mandatory. A weekly team meeting is mandatory
  • We build spec-first with AI in the loop. You write clear specs and direct AI coding agents, and you remain responsible for understanding everything that ships. You should be able to explain any of it and debug it quickly
  • We are iterative. Pick something up, close it, move on. We do not believe in long cycles
  • You are customer-facing: customer calls, customer emails, customer presentations

If you want a quiet, heads-down, low-communication role, this is not it.

08

Our hiring process

We move quickly and we tell you where you stand at every step.

  1. 01

    Submit your CV

    for screening.

  2. 02

    Short review task.

    We send you an example workflow with problems deliberately built into it. Review it and record a 2-minute Loom, camera and audio on, walking us through what is wrong, what is missing, and what you would ask before building it. There is no answer sheet to match. We are listening for how you think and how you communicate.

  3. 03

    Panel interview, 25 minutes.

    You meet the founder and three of our engineers covering browser automation, backend and front end, and AWS and DevOps. Fast paced and strictly timed, so short, clear, specific answers work in your favour.

  4. 04

    Offer or decline in the same week.

    Either way you get a clear answer, not silence.

Also openVoice AI EngineerOwn production voice agents, conversational state, telephony, and the backend tools behind every call.
Direct application

Show us what you have shipped.

Tell us about the most relevant production system you built end to end and the part you personally owned.

Keep it specific. We care about what ran in production, the decisions you made, and the problems you personally solved.

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