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Clera

Backend-Leaning Product Engineer

San FranciscoFrom $275kfulltimemidAdded today

About this role

Join an early-stage AI startup as a Backend-Leaning Product Engineer with end-to-end ownership of customer-facing features. You'll design and maintain backend systems, orchestration layers, and integrations while making independent product decisions alongside founders in a fast-moving San Francisco environment.

What you'll do

  • Own features end-to-end from design through shipping and iteration
  • Build and maintain backend systems, APIs, data models, and automation pipelines
  • Integrate with external tools, legacy systems, and third-party services
  • Design workflows and orchestration layers for AI/automation-driven products
  • Debug production issues and exercise engineering judgment under pressure
  • Collaborate directly with founders and customers on product decisions

What they're looking for

  • Backend systems design and implementation
  • Data modeling and schema design
  • API development
  • System integrations and third-party service connections
  • Production debugging and troubleshooting
  • Python
  • Automation pipeline design
  • Full-stack capability with backend focus

Benefits

  • Meaningful equity stake
  • High ownership and autonomy over features
  • Direct collaboration with founders
  • Hybrid in-office environment in San Francisco
  • Exposure to AI and automation product development
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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 shipped a customer-facing product in an ambiguous or messy startup environment—what was your role and what made it successful?
  • Tell us about a complex data model or automation pipeline you designed. What trade-offs did you make and why?
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