Platform Engineer

We run an agentic AI platform that acts as a personal advocate for rare disease patients. Our AI agent lives in your text messages, makes phone calls, automates browser sessions, maintains persistent memory across months of patient interactions, and coordinates multiple sub-agents to handle everything from appointment preparation to insurance navigation. The infrastructure challenge is unlike anything in traditional SaaS: long-running autonomous agent sessions with unpredictable compute patterns, real-time messaging at scale, tool-use pipelines that touch the open web on behalf of patients, and healthcare-grade compliance requirements across all of it.

We need someone to own this platform end-to-end.

We're hiring a Staff Platform Engineer to build and own the infrastructure that powers Citizen Health — the cloud platform, deployment systems, and reliability practices that let our teams ship AI-driven features safely 'll partner with teams across AI, web, mobile, and data engineering to keep our platform performant, secure, and compliant with healthcare standards (HIPAA, SOC 2, and adjacent frameworks).

This is a hands-on technical leadership role. You'll write code, set the direction for platform engineering, and raise the bar for how the entire org runs in production. You will likely be the first dedicated infrastructure hire and will build the platform engineering function from the ground up — owning everything from Terraform to on-call until you grow the team.

You'll report to the Director of Engineering.

Platform & infrastructure strategy — Set the technical direction for our agentic platform. Design architectures that handle long-running AI agent sessions, real-time Whats App message delivery, and autonomous tool execution (browser, phone, API calls) — all within HIPAA boundaries. Make the right build-vs-buy calls and keep infrastructure cost-efficient as we scale from hundreds to tens of thousands of active patients.

Reliability & observability — Define SLOs, build the observability stack, drive incident response, and keep uptime boringly high. Make on-call sustainable. When something breaks at 2am, you fix it, write the post-mortem, and spend the next sprint making sure it never happens again — without being asked.

CI/CD & developer experience — Own the deployment pipeline end-to-end. Eliminate friction in the inner and outer loops so teams can ship to production dozens of times a day with confidence. Our AI engineers should be thinking about models and prompts, not fighting deploys.

Inference cost & capacity management — AI inference is our largest variable cost. Partner with AI engineering to optimize model serving, manage GPU and compute capacity, negotiate vendor contracts, and make sure our unit economics work as we scale.

Security & compliance — Partner with security and legal to maintain HIPAA, SOC 2, and related regulatory standards. Implement controls that protect patient data without slowing teams down. Secure the agent tool-use pipeline — when our AI agent opens a browser or makes a phone call on behalf of a patient, the blast radius has to be contained.

Cross-functional partnership — Work closely with Product, AI/ML, Data, and Security to translate platform needs into roadmap. Unblock teams and mentor engineers across the org.

You’ve been the person who saw a scaling wall six months before it became a crisis, made the case to rearchitect, and then did the work. You’ve led infrastructure through a meaningful inflection — 10x traffic growth, launch into a new channel, migration from monolith to services — and you can talk concretely about what broke, what you learned, and what you’d do differently.

You thrive in early-stage…