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Clera

Founding Design Engineer

San Francisco$180k–$220kfulltimemidAdded today

About this role

A founding frontend engineer role at a seed-stage AI SaaS startup focused on intelligent pricing. You'll own the design system end-to-end, establish frontend standards for a small team, and ensure both human and AI-generated code maintains consistent quality and coherence.

What you'll do

  • Own the design token system, component library, and Tailwind conventions across the product
  • Define patterns using React Query, React Hook Form, and Zod to ensure agent-written code integrates seamlessly
  • Audit and maintain frontend tooling, Biome configuration, Playwright tests, and performance
  • Enforce WCAG accessibility standards and integrate brand guidelines into the codebase
  • Collaborate with AI coding tools to review and improve agent-generated UI contributions
  • Build conversational and streaming AI interface patterns for B2B users

What they're looking for

  • React and TypeScript
  • Tailwind CSS and design systems
  • Component libraries (shadcn/ui, Radix UI)
  • Design tokens and component abstractions
  • AI coding assistants (Claude, Cursor)
  • Playwright and frontend testing
  • WCAG accessibility standards
  • Framer Motion or animation libraries

Benefits

  • Equity at founding team level
  • Seed-stage startup with significant ownership and impact
  • On-site in San Francisco with flexible relocation support
  • Opportunity to shape product identity and standards
  • Work with cutting-edge AI integration in production
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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

  • Describe a design system or component library you owned in production—how did you maintain consistency as the codebase scaled?
  • How have you used AI coding assistants in real workflows, and what patterns did you establish to maintain quality in generated code?
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