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Clera

Backend-Leaning Product Engineer

San FranciscoFrom $275kfulltimemidAdded today

About this role

Join a small, fast-moving startup as a backend-leaning product engineer where you'll own customer-facing AI and automation features end-to-end, making independent technical and product decisions with minimal oversight. This role combines full-stack ownership with a strong backend focus, requiring you to build systems, integrate third-party services, and ship real products in a high-ambiguity, founder-driven environment.

What you'll do

  • Own features end-to-end from design through shipping, iteration, and production support
  • Build and maintain backend systems, APIs, data models, and automation pipelines
  • Design workflows and orchestration for AI/automation-driven products
  • Integrate external tools, legacy systems, and third-party services
  • Debug production issues and apply engineering judgment under pressure
  • Collaborate with founders, customers, and cross-functional teams in a hybrid SF setting

What they're looking for

  • Backend systems design and API development
  • Data modeling and automation pipeline design
  • Third-party integrations and legacy system integration
  • Production debugging and troubleshooting
  • Full-stack development (with backend emphasis)
  • AI/LLM and workflow orchestration (agentic workflows, RAG)
  • Python or modern web/backend frameworks
  • Product thinking and independent decision-making

Benefits

  • Meaningful equity in early-stage startup
  • High ownership and autonomy over features
  • Work directly with founders and customers
  • Hybrid work arrangement in San Francisco
  • Opportunity to shape products in 0-to-1 phase
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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

  • Tell us about a product you shipped end-to-end in an early-stage or ambiguous environment — what was your biggest challenge?
  • Describe your experience designing data models and automation pipelines. What trade-offs did you make?
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