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Clera

Founding Agentic Engineer

San Francisco$150k–$300kfulltimemidAdded today

About this role

Join this early-stage startup as a founding engineer to architect and own the agent layer of a production agentic platform serving real-world markets. You'll design context systems, self-healing workflows, and the runtime harness that powers autonomous agents handling shift staffing, logistics, and labor operations—working directly with the CTO from day one.

What you'll do

  • Own the end-to-end agent layer including context engineering, self-learning systems, evaluation frameworks, and harness architecture
  • Design and build a compounding knowledge base that improves agent integration capabilities as the system scales
  • Create self-healing workflow patterns that detect, diagnose, and autonomously recover from production failures
  • Establish engineering standards, patterns, and best practices for how all agents across the company are built and measured
  • Collaborate with founders on rapid experimentation and technical product direction for agentic systems
  • Contribute to hiring and eventually lead the team building agentic infrastructure

What they're looking for

  • Agentic software development (recent, hands-on experience within past year)
  • Agent harness architecture and context engineering
  • Agent tracing and evaluation frameworks
  • TypeScript and Effect-TS
  • PostgreSQL database design
  • LLM integration and agent framework expertise
  • Production system design and debugging
  • Eval-driven development and iteration

Benefits

  • Founding engineer equity participation
  • Competitive salary range of $150,000–$300,000 based on experience
  • Visa sponsorship available
  • Work directly with founders and shape technical direction
  • On-site 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

  • Walk us through a recent agentic system you built in production—what was the hardest part of the context engineering?
  • How have you approached evaluation and iteration for agent behavior, and what frameworks or methodologies did you use?
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