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Clera

Founding Product Engineer

San Francisco$200k–$250kfulltimemidAdded today

About this role

Join an early-stage B2B SaaS startup as a founding product engineer to design and ship end-to-end AI-driven pricing and monetization platform modules. You'll work across full-stack architecture, React UIs, and agentic AI systems while partnering directly with customers and leadership to build financial-grade software.

What you'll do

  • Own entire product modules from design through deployment, including versioned APIs and React frontends
  • Design agentic AI systems spanning Slack bots, terminal interfaces, web surfaces, and vendor integrations
  • Architect backend services and pricing ontologies using Pydantic to enforce financial correctness
  • Build MCP/FastMCP servers enabling LLM agents to operate features via conversational interfaces
  • Lead architectural reviews and establish testing, observability, and deployment practices
  • Mentor peers, influence product strategy, and drive engineering culture at an early-stage company

What they're looking for

  • FastAPI and Python backend development
  • MongoDB (or comparable database)
  • React and TypeScript UI development
  • REST/GraphQL API design and versioning
  • LLM agents, tool-use, and MCP integration
  • B2B SaaS monetization and pricing concepts
  • Financial logic correctness and production debugging
  • Full-stack product ownership in ambiguous environments

Benefits

  • Equity participation at founding-team level
  • Direct influence on product strategy and architecture
  • Work on AI-native development practices and tooling
  • Mentor and leadership opportunities from day one
  • On-site collaboration in San Francisco with early 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.

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Likely interview questions

  • Walk us through a product module you owned end-to-end; how did you handle the ambiguity between technical feasibility and customer needs?
  • Describe your experience building financial or monetization logic in production. How do you ensure correctness?
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