Staff Platform Engineer

What You'll Drive

• 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.
• 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.

Who You Are

• 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 environments where the team is small, the scope is broad, and the best answer hasn't been written in a runbook yet.
  • You default to data, automate the toil, and document what you learn.
• You've worked at a startup before (ideally sub-50 people) and you liked it.
  • You're excited about the chance to build platform infrastructure for an agentic AI system that doesn't exist anywhere else — the playbook hasn't been written yet.

Must-Have Skills

• 8+ years of software / infrastructure engineering experience; 4+ years in a senior IC or technical leadership role on a Platform, SRE, or DevOps team.
  • Deep expertise running production systems on a major cloud provider (AWS, GCP, or Azure).
• Hands-on with Kubernetes, infrastructure-as-code (Terraform, Pulumi, or similar), and modern CI/CD tooling (GitHub Actions, ArgoCD, Spinnaker, etc.).
  • Strong programming skills in at least one of Go, Python, or TypeScript — you build tooling, not just configure it.
• Demonstrated experience scaling infrastructure through a significant growth inflection (10x users, new product surface, architectural migration) in a production environment.
  • Proven track record designing for high availability, zero-downtime releases, and graceful degradation in regulated or data-intensive environments.
• Strong security fundamentals: IAM, secrets management, network segmentation, vulnerability management, supply-chain security.
  • Experience at an early-stage or high-growth startup where you owned infrastructure broadly, not just a narrow slice.
• Excellent written and verbal communication — you're equally effective in a post-mortem, a roadmap discussion, and a Slack thread.
  • You're comfortable owning the platform engineering function and driving its growth from the ground up.

Preferred Skills

• Experience supporting AI/ML workloads in production — model serving, inference optimization, GPU infrastructure, vector databases, or large-scale data pipelines.
  • This is close to a must-have given our architecture.
• Familiarity with agentic AI systems, multi-agent orchestration, or long-running autonomous workflows.
  • Experience with messaging infrastructure at scale — message queues, webhook reliability, delivery guarantees, rate limiting (WhatsApp, SMS, or similar).
• Background in healthtech, life sciences, fintech, or other regulated domains (HIPAA, SOC 2, HITRUST, FedRAMP).
  • Experience growing a Platform or SRE function from a small group of generalists into a specialized team.