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Clera

Product Engineer (Mid-Level)

San Francisco$150k–$300kfulltimemidAdded today

About this role

Join an early-stage AI-driven talent acquisition platform as a Mid-Level Product Engineer, owning features end-to-end from design through production. You'll work directly with founders and product to build user-facing experiences that integrate LLM capabilities, balancing full-stack development across TypeScript, React, Python/Node.js, and cloud infrastructure.

What you'll do

  • Own complete product features from scoping and API design to production deployment
  • Design and implement scalable backend services, data schemas, and operational tooling
  • Develop frontend experiences in React/Next.js and integrate LLM/AI capabilities into product flows
  • Collaborate with founders, product, and design to prioritize work and define success metrics
  • Participate in architecture and roadmap discussions, making pragmatic tradeoffs for early-stage growth
  • Ship user-facing experiences that balance usability and performance, iterating on feedback

What they're looking for

  • TypeScript and React/Next.js
  • Python or Node.js backend development
  • PostgreSQL and relational database design
  • AWS or GCP cloud platforms
  • LLM and AI service integration
  • API design and data modeling
  • CI/CD, monitoring, and testing
  • Full-stack development and DevOps

Benefits

  • Early-stage equity opportunity
  • Salary range $150,000–$300,000 per year
  • On-site role in San Francisco with direct founder/product collaboration
  • End-to-end ownership of impactful features
  • Opportunity to shape technical direction and product roadmap
  • Fast-moving team environment with minimal process overhead
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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 recent feature you shipped end-to-end; walk us through your API design decisions and how you measured success.
  • Tell us about a time you integrated an LLM or AI service into a production application—what were the key challenges and how did you solve them?
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