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Clera

Backend Engineer

remote (Remote)$127k–$160kfulltimemidAdded today

About this role

A senior backend engineering role at a fintech company building compliance infrastructure. You'll design scalable, high-trust systems and APIs while shaping engineering practices on a collaborative, experienced team.

What you'll do

  • Design and build clean, testable backend systems and APIs for compliance workflows
  • Architect scalable infrastructure for high-volume and high-trust distributed platforms
  • Establish and maintain strong testing, quality, and maintainability standards
  • Analyze complex product challenges through deep systems and user-needs thinking
  • Lead technical culture and engineering practices through collaboration and mentorship

What they're looking for

  • Backend engineering (5–7+ years production experience)
  • Node.js, TypeScript, Python, Go, or Java
  • Relational databases (Postgres or MySQL)
  • Message queues and event-driven architectures (RabbitMQ, Kafka)
  • Containerization and cloud platforms (Kubernetes, AWS)
  • API design and scalable infrastructure
  • Automated testing and test-driven development
  • Systems thinking and architectural reasoning

Benefits

  • Fully remote work in European time zones
  • Transparent, level-based compensation with no individual negotiations
  • Regular in-person team offsites
  • Work in regulated fintech domain
  • Collaborative, senior-focused engineering team
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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 backend system you designed—what were the key architectural decisions and trade-offs?
  • Describe your experience with event-driven architectures or message queues in production—what challenges did you encounter?
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