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Clera

Founding Engineer - Infrastructure

San Francisco$175k–$300kfulltimemidAdded today

About this role

Founding infrastructure engineer at a seed-stage AI integration platform, reporting to the CTO with a clear path to leadership. You'll design and operate a durable-execution runtime, scale agent infrastructure, build observability pipelines, and ship a self-hostable product while setting engineering standards for the domain.

What you'll do

  • Design and operate a sandboxed, durable-execution integration runtime for production workloads
  • Build and scale infrastructure for AI coding agents that write, test, and deploy integration code
  • Own the full observability pipeline including logs, metrics, and tracing across all integrations
  • Ship a self-hostable, single-tenant deployment of the platform as a first-class product
  • Establish engineering patterns and infrastructure standards across the organization
  • Hire and mentor infrastructure engineers as the team scales over the first year

What they're looking for

  • Kubernetes operations and production debugging at scale
  • Cloud infrastructure design and end-to-end platform ownership
  • Observability architecture (logs, metrics, tracing)
  • TypeScript and PostgreSQL
  • AWS and Docker
  • Self-hosted deployment systems
  • Distributed systems and durable execution patterns
  • AI-assisted engineering workflows

Benefits

  • Competitive base salary ($175,000–$300,000 annually)
  • Visa sponsorship including O-1 visa pathways
  • Founding engineer equity and leadership track
  • Direct collaboration with founding team and CTO
  • Fast-paced, ambiguous, high-impact environment
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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

  • Walk us through a time you owned infrastructure end-to-end in production—what were the hardest problems you solved?
  • Describe your experience operating Kubernetes at scale: what failures did you encounter and how did you debug them?
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