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HarperHarperSan Francisco, CA

Platform Engineer

Build and own core infrastructure, observability, and tooling for a hyper-growth AI insurance platform running 200+ services and thousands of daily agentic AI decisions. Focus on scale, reliability, developer velocity, and AI eval systems.

140k – 280k/yr
On-site5+ YOEDevOps / SRE

About the role

What You'll Do

  • Own core infrastructure — Databases, AWS services, networking, CI/CD; the systems every engineer depends on
  • Build for scale — Thousands of concurrent AI operations, sub-second response times, cost-effective under load
  • Design observability that works — System-level errors AND business-level silent-failure detection; we find out something is broken from an alert, not from a person hours later
  • Orchestrate agentic workloads — N parallel agent instances doing non-deterministic work, running reliably and cost-effectively as N grows
  • Multiply developer velocity — The tooling and abstractions that let product engineers ship in days instead of weeks
  • Own reliability end-to-end — SLOs, on-call, incident response, and the post-mortems that make it rarer next time
  • Build the eval infrastructure — Systems that measure whether AI outputs are getting better, not just running

Requirements

  • Software engineering experience with a platform, infrastructure, or SRE focus (level determined during interviews)
  • Proficiency in Python, TypeScript, Go, or similar
  • Production experience with cloud infrastructure (AWS), databases (Postgres), and observability tooling
  • Track record of building systems and tooling that other engineers depend on
  • Based in San Francisco or willing to relocate

Nice to Have

  • Experience orchestrating AI/ML workloads at scale (agent frameworks, LLM inference infrastructure)
  • Voice AI or real-time systems experience
  • Deep AWS experience (ECS, Lambda, RDS, VPC design)
  • Prior startup experience—especially at companies that scaled through hypergrowth

Compensation & Logistics

Salary: $140,000–$280,000 depending on experience + performance bonuses & equity Location: San Francisco, in-office. Based in SF or willing to relocate. Schedule: Monday–Friday, very early morning start, in-office five days a week. Benefits: Uber commuter benefits; breakfast, lunch, and dinner provided; snacks, drinks, and coffee daily; free gym membership; health, dental, and vision insurance.

Skills

AWSPythonTypeScriptGoPostgresObservabilityCI/CDSREDatabasesNetworking

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