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Clera

Founding Engineer

San Francisco$150k–$250kfulltimemidAdded today

About this role

Join an early-stage agentic integration platform as the founding engineer, owning the complete technical foundation from agent platform and infrastructure through production systems. You'll work directly with founders to establish engineering standards and ship reliable systems serving enterprise customers.

What you'll do

  • Design and own the agent platform, infrastructure, and integrations runtime end-to-end
  • Establish engineering patterns, standards, and best practices for future team growth
  • Build and maintain reliable, observable production systems with continuous deployment
  • Collaborate with founders on technical decisions and product direction
  • Implement observability, monitoring, and distributed systems reliability patterns
  • Develop full-stack features spanning frontend, backend, and cloud infrastructure

What they're looking for

  • TypeScript (full-stack)
  • React
  • Node.js
  • AWS cloud infrastructure
  • PostgreSQL database design
  • LLM and agent platform integration
  • Distributed systems and observability
  • Production system architecture

Benefits

  • Equity opportunity as founding engineer
  • Work directly with founders shaping company direction
  • Shape technical culture and engineering standards from day one
  • Visa sponsorship available for O-1 candidates
  • On-site position 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.

View all jobs at Clera

Likely interview questions

  • Tell us about a zero-to-one project you built—what was your approach to architectural decisions early on?
  • Describe your experience integrating with LLMs or building agent-based systems. What challenges did you encounter?