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Clera

Product Engineer

San Francisco$150k–$200kfulltimemidAdded today

About this role

Join an early-stage ambient AI startup as a generalist product engineer owning the full app experience across iOS, Apple Watch, and Mac. You'll ship user-facing features rapidly while working directly with product leadership, integrating LLM-based capabilities into a consumer product with minimal bureaucracy.

What you'll do

  • Own end-to-end feature development across iOS, watchOS, and Mac platforms
  • Ship user-facing improvements addressing real product issues from early users
  • Integrate agent and LLM-based features including tool use, memory, and retrieval
  • Make independent scope and design tradeoffs across UX, UI, backend, and AI/ML
  • Collaborate with backend specialist on shared services powering multiple clients
  • Iterate features based on user feedback without extensive specification or approval cycles

What they're looking for

  • Swift and SwiftUI for iOS and watchOS
  • TypeScript and React for web/desktop
  • Electron for Mac desktop development
  • LLM and agent integration in production apps
  • Backend API design and shared services
  • Full-stack product development across platforms
  • Real-time or streaming systems (audio, live data)
  • Cross-platform UX/UI design sensibility

Benefits

  • Equity compensation package
  • Hybrid work arrangement (3 days/week in-office)
  • Direct collaboration with product leadership
  • Autonomy to make and own product decisions
  • Early-stage startup with significant impact potential
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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 shipped consumer app feature you built end-to-end—what technical decisions did you make and why?
  • Describe your experience integrating LLM or agent-based functionality into a production consumer app. What were the main challenges?
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