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Clera

Founding Engineer

San Francisco$140k–$220kfulltimemidAdded today

About this role

Join an early-stage B2B SaaS startup as the first engineering hire, building AI-powered workflow automation for distributors and manufacturers. You'll own full-stack development across customer-facing features, AI agents, and integrations while working directly with founders and customers.

What you'll do

  • Conduct customer discovery to understand workflows and identify problems to solve
  • Build full-stack features spanning frontend, AI agents, third-party integrations, and infrastructure
  • Design and implement customer-driven features end to end from conception to production
  • Develop and improve evaluation frameworks, tests, and tooling for faster customer implementations
  • Deploy and manage applications on Google Cloud Platform
  • Own a meaningful product surface area with end-to-end responsibility within first quarter

What they're looking for

  • TypeScript and Next.js for full-stack web development
  • Python for backend and AI agent development
  • Production-ready AI agent design and implementation
  • Google Cloud Platform deployment and management
  • Third-party API integration and legacy system integration
  • Automated testing and evaluation frameworks
  • LLM frameworks and prompt engineering
  • Customer discovery and business problem translation

Benefits

  • Early-stage startup equity opportunity
  • Direct impact owning meaningful product areas
  • Work directly with founders and customers
  • Visa sponsorship available
  • On-site in San Francisco
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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 production AI agent system you've built—how did you design the context engineering and evaluation framework?
  • Describe your experience integrating legacy enterprise systems or ERPs. What was the most complex integration you shipped?