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Clera

Founding Product Engineer

San Francisco$140k–$180kfulltimemidAdded today

About this role

Join a seed-stage legal AI startup as a founding product engineer to build full-stack features that transform legal workflows. You'll work alongside AI engineers and attorneys in a high-ownership role, shaping both the product and engineering culture from the ground up.

What you'll do

  • Build and own full-stack product features from data models through user interfaces
  • Collaborate with AI engineers and attorneys to translate legal workflows into production software
  • Make pragmatic architecture decisions balancing speed with long-term maintainability
  • Write clean, reliable code and take complete ownership of production features
  • Define engineering culture, coding standards, and hiring practices as the team scales
  • Ship customer-focused work in a fast-paced, high-ownership environment

What they're looking for

  • Full-stack development (TypeScript/React, modern backend, relational databases)
  • Production AI/LLM integration
  • End-to-end feature ownership and deployment
  • Architecture and engineering trade-off decisions
  • Product instincts and customer-first thinking
  • Ability to work with domain experts and translate complex workflows
  • DevOps and CI/CD practices
  • Comfort with ambiguity and minimal process

Benefits

  • Founding role with significant influence over engineering culture and standards
  • Opportunity to shape product direction and company trajectory
  • Work on meaningful legal tech problems with domain experts
  • On-site in San Francisco with full-time commitment
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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 full-stack feature you shipped from conception to production—what trade-offs did you make?
  • Describe your hands-on experience building with LLMs or AI. What challenges did you encounter?
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