Platform & infrastructure strategy — Set the technical direction for our agentic platform. Design architectures that handle long-running AI agent sessions, real-time WhatsApp 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.