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Clera

Founding Engineer ($3M pre-seed)

Palo Alto (Remote)fulltimemidAdded 1 month ago

About this role

Join Clera as engineer #4 to build AI-powered recruiting automation that disrupts a $600B industry. You'll have full ownership of product areas, ship to production daily, and work alongside experienced founders in a SF hackerhouse with $3M pre-seed funding and paying customers.

What you'll do

  • Own entire product features from concept through deployment with direct impact on product direction
  • Build agentic AI systems that automate complex recruiting workflows end-to-end
  • Ship production code daily and iterate rapidly based on customer feedback
  • Collaborate closely with CTO and founding engineering team on technical strategy
  • Scale systems from early-stage to handle thousands of weekly user engagements
  • Transition code from rapid prototyping to production-grade quality as needed

What they're looking for

  • TypeScript and React
  • AI/LLM API integration and implementation
  • AI-assisted coding with tools like Cursor
  • Full-stack development and system design
  • Startup mentality with high agency and resourcefulness
  • Customer-focused iteration and feedback incorporation
  • Database and backend technologies (Supabase, Prisma, Typesense)

Benefits

  • Meaningful equity stake in fast-growing startup
  • Competitive salary with significant equity package
  • Live and work in SF hackerhouse with zero commute
  • True ownership with no micromanagement
  • Visa support available
  • Work with experienced founders and A-player 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.

View all jobs at Clera

Likely interview questions

  • Walk us through a recent project where you built and shipped a feature end-to-end. How did you decide what to build first, and how quickly did you get it to production?
  • Tell us about your experience working with LLM APIs and AI-powered features. What's a project where you've integrated AI into a product, and what challenges did you face?
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