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Clera

Founding Engineer

San Francisco$150k–$220kfulltimemidAdded 1 month ago

About this role

Join a seed-funded B2B SaaS startup as a Founding Engineer to build core infrastructure for an AI agents and people-data platform. You'll work directly with the founding team owning critical systems, APIs, and LLM workflows while scaling toward Series A.

What you'll do

  • Design and build core infrastructure including APIs, LLM-powered workflows, web scraping systems, and knowledge graph architecture
  • Architect production-grade systems handling millions of API requests with focus on performance, cost efficiency, and reliability
  • Own projects end-to-end from problem definition through deployment and iteration
  • Collaborate with CEO and CTO on technical strategy, roadmap priorities, and architectural decisions
  • Contribute across the full stack including documentation, tutorials, and internal tooling
  • Stress-test and showcase APIs through experimental builds

What they're looking for

  • Full-stack or backend software engineering (2+ years)
  • JavaScript and TypeScript proficiency
  • Agent orchestration, LLMs, or web scraping experience
  • Linux server administration in production environments
  • Distributed systems and microservices architecture
  • Cloud infrastructure (AWS/GCP)
  • Strong computer science fundamentals
  • End-to-end product development experience

Benefits

  • Competitive salary: $150,000–$220,000 USD annually
  • Equity participation as founding team member
  • Direct collaboration with CEO and CTO
  • Shape technical strategy and long-term architecture
  • 5-day on-site work in San Francisco
  • Opportunity to build at an early-stage, well-backed startup
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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 production system you built end-to-end. What was your biggest architectural decision, and how would you approach it differently now?
  • Describe your experience with LLM-powered workflows or agent orchestration. What challenges did you encounter, and how did you solve them?
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