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Clera

Founding Engineer

San Francisco$175k–$225kfulltimemidAdded 1 month ago

About this role

Join an early-stage consumer AI startup as a Founding Engineer building a real-time platform that makes AI interactions feel personal and present. You'll architect core systems from the ground up, work directly with founders, and help establish engineering culture while integrating advanced video and audio AI models.

What you'll do

  • Build full-stack features collaborating with founders, designers, and engineering team
  • Design and implement memory, retrieval, proactivity, and AI responsiveness systems
  • Integrate real-time video generation and audio synthesis models from internal and third-party sources
  • Set engineering quality standards and actively recruit world-class talent
  • Use the product extensively to validate user value and ensure quality
  • Establish technical foundations and architecture for early-stage product

What they're looking for

  • Python (including typed scientific Python)
  • Full-stack software engineering
  • Computer Science fundamentals
  • Real-time media systems (bonus)
  • Video/vision model deployment (bonus)
  • Audio synthesis (bonus)
  • Memory systems architecture (bonus)
  • AI-assisted development workflows (bonus)

Benefits

  • Salary: $175,000–$225,000 USD annually
  • Visa sponsorship available
  • Founding team influence on product and culture
  • On-site in San Francisco, CA
  • Early-stage equity opportunity (implied)
  • Direct collaboration with founders in fast-moving environment
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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 technically complex side project you've built. What was the hardest problem you solved, and how did you approach it?
  • Tell us about your experience with real-time systems or media pipelines. How have you handled latency constraints in production?
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