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Clera

Founding Engineer - Infrastructure

San Francisco$175k–$300kfulltimemidAdded today

About this role

Be the first infrastructure engineer at an early-stage AI agent integration platform, owning the entire platform layer from durable execution runtime to observability. You'll work directly with the CTO on a leadership track, establishing foundational patterns while shipping production infrastructure for a scaling team.

What you'll do

  • Design and build a mini cloud platform for durable execution, sandboxed isolation, and self-healing infrastructure
  • Architect agent infrastructure enabling coding agents to write, test, and deploy integration code at production scale
  • Implement comprehensive observability pipelines including logs, metrics, and distributed tracing across integrations
  • Deliver a single-tenant, self-hostable product deployment with end-to-end observability
  • Define engineering patterns and standards for future infrastructure team members to follow
  • Recruit and lead the infrastructure team as it grows over the next year

What they're looking for

  • Kubernetes and container orchestration
  • AWS cloud infrastructure
  • TypeScript backend development
  • PostgreSQL database design
  • Observability systems (logging, metrics, tracing)
  • Durable workflow or execution runtime design
  • Docker and containerization
  • Technical leadership and team mentorship

Benefits

  • Leadership track with clear path to leading infrastructure team
  • High ownership and high-impact first infrastructure role
  • Visa sponsorship available
  • Work directly with CTO on foundational platform decisions
  • Early-stage startup equity opportunity (implied)
  • On-site collaboration in San Francisco
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Describe a time you designed an observability pipeline from scratch—what metrics and traces did you prioritize first, and why?
  • Walk us through your experience with durable execution or workflow orchestration systems. What trade-offs did you navigate?
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