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Clera

Founding Engineer ($3M pre-seed)

Houston (Remote)fulltimemidAdded 1 month ago

About this role

Join Clera as engineer #4 to build AI-powered recruiting automation at a pre-seed startup with $3M funding. You'll own full product areas, ship daily, and help disrupt a $600B industry alongside experienced founders and A-player engineers in a San Francisco hackerhouse.

What you'll do

  • Ship production features daily and own entire product areas from concept to deployment
  • Build agentic AI systems that automate complex recruiting workflows
  • Work directly with CTO and founding engineers on product direction and technical decisions
  • Iterate on product based on customer feedback and market needs
  • Scale systems from early traction to handle growth and increased quality demands
  • Collaborate closely with team in shared hackerhouse environment

What they're looking for

  • TypeScript and React
  • Experience coding with AI tools (Cursor)
  • LLM APIs and AI integration
  • Full-stack development (Supabase, Prisma, Typesense)
  • Product ownership and entrepreneurial mindset
  • Fast prototyping and iteration
  • Customer engagement and feedback incorporation
  • Startup execution and resourcefulness

Benefits

  • Meaningful equity stake
  • Competitive salary
  • Full product ownership and decision-making authority
  • Zero-commute hackerhouse setup in San Francisco
  • Work with experienced founders and A-player team
  • Visa sponsorship support
  • Daily shipping to production with high impact
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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.

View all jobs at Clera

Likely interview questions

  • Walk us through a project where you built with AI tooling like Cursor. How did it change your development workflow, and what were the tradeoffs between moving fast and code quality?
  • Tell us about your experience integrating with LLM APIs. What was challenging, and how did you handle prompt engineering or token optimization in production?
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