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Clera

Founding Engineer (AI/ML)

San Francisco$130k–$170kfulltimemidAdded today

About this role

Join a pre-seed AI recruiting marketplace as a Founding Engineer to build the intelligence layer powering candidate-role matching. You'll own recommendation systems, LLM-driven features, and production ML infrastructure while shipping end-to-end product features alongside the founding team.

What you'll do

  • Build and own recommendation engines and ranking algorithms that drive matching outcomes
  • Develop LLM-powered features using LLM APIs to improve candidate-role alignment
  • Architect and maintain production data pipelines and services across the full stack
  • Ship end-to-end product features to production on a rapid, daily cadence
  • Collaborate cross-functionally to translate product goals into scalable features

What they're looking for

  • LLM APIs and LLM-powered feature development
  • Recommendation systems and ranking algorithms
  • TypeScript and React in production
  • Supabase and Prisma
  • Typesense or similar search/ranking infrastructure
  • Workflow automation tools (trigger.dev)
  • Database design and data pipelines
  • CS fundamentals and problem-solving

Benefits

  • Visa sponsorship available
  • High ownership in a founding engineer role
  • Hybrid work in San Francisco with in-person collaboration
  • Opportunity to shape core product direction at pre-seed stage
  • Fast-paced, iterative startup 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.

View all jobs at Clera

Likely interview questions

  • Describe a production LLM-powered feature you've built—what challenges did you face with latency, cost, or quality?
  • Walk us through how you'd design a candidate-role matching system from scratch, covering data pipelines, ranking, and inference.
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