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Clera

Founding Engineer

New York (Remote)$156k–$182kfulltimemidAdded today

About this role

Join a Y Combinator-backed fintech/healthtech AI startup as one of three founding engineers. You'll build the infrastructure and systems powering AI agents that transform disparate data sources into continuously updated industry models, starting with healthcare.

What you'll do

  • Build full-stack features including frontend, real-time systems, and backend infrastructure
  • Design and maintain data pipelines and internal tools for analysts to onboard new data sources
  • Improve agentic parsing and extraction systems to enhance AI reliability and capability
  • Own production systems end-to-end: data inspection, QA, instrumentation, deployment, and incident response
  • Ship rapid iterations: add new data source day one, improve agentic systems week one, deliver company ontology within 30 days
  • Operate and monitor distributed systems in production with strong observability practices

What they're looking for

  • Python backend development (FastAPI or similar)
  • TypeScript and React frontend development
  • LLM and agentic AI systems in production
  • Data pipelines, ETL, and SQL modeling
  • PostgreSQL database design and optimization
  • AWS cloud infrastructure and deployment
  • Real-time data systems and streaming
  • Production monitoring, observability, and debugging

Benefits

  • Equity stake as founding engineer at early-stage startup
  • Full-stack ownership and direct product impact from day one
  • Work with cutting-edge AI/agentic technology
  • Collaborative small founding team environment
  • On-site collaboration in New York City
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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

  • Tell us about a production LLM or agentic AI system you've built—what were the biggest challenges with reliability and extraction quality?
  • Describe your experience designing data pipelines and ETL systems. How did you approach data quality and source onboarding at scale?
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