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NewsBreak

AI Engineer — AI-Native Product Engineering

Mountain View, California, United States$118k–$212kfull-timemidAdded today

About this role

NewsBreak is seeking an AI Engineer to build user-facing products end-to-end using AI-native development practices. You'll own features from frontend architecture through backend integration, leveraging coding agents and modern AI tools while maintaining production quality standards at scale.

What you'll do

  • Build and ship complete user-facing features from product requirements through testing, rollout, and monitoring
  • Use AI coding agents and tools as core development workflow to generate, refactor, test, and debug code
  • Own frontend architecture, component systems, and testing patterns for consumer-scale products
  • Work across frontend and backend boundaries, making API and service changes needed to complete product experiences
  • Set quality standards for AI-generated code through critical review, automated testing, and staged rollouts
  • Investigate production issues, regressions, and incidents using observability and AI-assisted debugging

What they're looking for

  • JavaScript/TypeScript
  • React or modern frontend frameworks
  • Full-stack product engineering (frontend and backend)
  • AI coding tools and agents
  • API design and backend services
  • Testing, performance optimization, and observability
  • System debugging and reliability engineering
  • Quick learning of unfamiliar technologies

Benefits

  • Work at a unicorn company with 40M+ monthly active users
  • Great Place to Work® certified
  • Discretionary bonus and equity options eligible
  • Fast Company Top Innovators recognition
  • High-growth, fast-moving environment with autonomy
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NewsBreak

NewsBreak operates a news and local marketplace platform serving 40M+ monthly active users, leveraging machine learning and data infrastructure to power recommendations, advertising, and matching between consumers and businesses. The company is hiring software engineers, ML engineers, and data specialists to build and optimize backend systems, ML infrastructure, recommendation engines, and algorithms that drive user engagement and monetization.

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Likely interview questions

  • Walk us through a production feature you shipped end-to-end that required both frontend and backend changes—how did you approach the architecture?
  • How have you integrated AI coding tools into your actual development workflow, and what challenges did you encounter?