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Clera

Product Engineer (Software Engineer)

San Francisco$120k–$200kfulltimemidAdded today

About this role

Join a Series A fintech startup as a full-stack product engineer to build consumer financial tools like cash advances and credit-building features. You'll own features end-to-end, from backend logic to API integrations, shipping daily to production in a fast-paced environment.

What you'll do

  • Design and implement end-to-end product features including domain models, business logic, and API integrations
  • Evaluate product and system performance using SQL, analytics tools, and data pipelines
  • Test and debug complex state machines in event-driven, pub/sub backend architectures
  • Ship to production daily via CI/CD pipelines and respond to production incidents
  • Drive incremental, data-driven releases aligned with product milestones
  • Collaborate with product, engineering, and business leaders on high-impact features

What they're looking for

  • Backend development (3+ years production experience)
  • RESTful API design and consumption (authentication, authorization, rate limiting)
  • Event-driven architectures and message queues (Kafka, Pub/Sub)
  • SQL and relational databases (PostgreSQL, MySQL)
  • CI/CD pipelines and automated testing
  • State machine debugging in distributed systems
  • Computer science fundamentals (algorithms, data structures, system design)
  • Cross-functional communication and technical translation

Benefits

  • Competitive salary of $120,000–$200,000 annually
  • Visa sponsorship available
  • On-site location in San Francisco with rapid shipping culture
  • Early-stage startup equity and growth opportunities
  • Direct impact on consumer financial wellbeing
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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 complex end-to-end feature you shipped in production—what were the key technical decisions?
  • Describe your experience debugging state machines in event-driven systems. What was the most challenging scenario you encountered?
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