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Clera

Forward Deployed Engineer

San Francisco$110k–$180kfulltimemidAdded today

About this role

Join an early-stage Y Combinator insurtech startup as a Forward Deployed Engineer, owning customer deployments of AI agents from initial scoping through production. You'll work directly with insurance agencies to integrate AI solutions into their existing systems, diagnose issues, and drive platform improvements based on real-world usage patterns.

What you'll do

  • Own end-to-end customer deployments from scoping through go-live, working directly with agency stakeholders
  • Build and maintain integrations with customer systems, including legacy systems with poor or nonexistent documentation
  • Design system solutions based on tribal knowledge extracted from domain experts and customer workflows
  • Diagnose and resolve production issues, delivering customizations that fit real operational needs
  • Identify account expansion opportunities by analyzing deployment patterns and maintaining customer relationships
  • Travel to customer sites to ensure successful deployments and sustained adoption

What they're looking for

  • Python production development
  • LLM applications and prompt engineering
  • AI agent development and deployment
  • API design and multi-system integrations
  • LLM evaluation design and iteration
  • Legacy system reverse-engineering
  • Cross-functional communication (technical and non-technical)
  • Voice/telephony stacks (Twilio or similar)

Benefits

  • Equity stake in Y Combinator-backed startup
  • Hands-on influence over platform product direction
  • Exposure to real-world AI deployment challenges
  • Customer-facing role with direct impact on business growth
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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 production AI application you've deployed to real users — what were the key challenges in getting it to work reliably?
  • Tell us about a time you had to integrate with a poorly documented or legacy system. How did you approach it?
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