AI Engineer

As an AI Engineer on NewsBreak’s AI-Native Product Engineering team, you will build and ship user-facing features using coding agents as a core development tool. The role is frontend-leaning, with end-to-end ownership spanning architecture, APIs, backend services, testing, rollout, and production outcomes.

Role Focus

NewsBreak is rethinking software development in an AI-native world, where AI increasingly supports how teams design, build, test, debug, and operate systems. Engineers on this team work with coding agents to ship production products quickly, while defining the architecture, context, quality standards, and guardrails required for reliable AI-generated software. This position starts from strong client-side product engineering skills and extends into adjacent stack areas, including APIs, backend services, data flows, and developer tooling.

Key Responsibilities

• Build user-facing products end to end by owning features from product requirements and frontend architecture through API integration, backend changes, testing, rollout, and production metrics.
• Use AI as a core development tool by working with coding agents to generate, refactor, test, and debug code, providing the context and validation required for production-quality results.
• Own frontend architecture and product quality by developing maintainable component systems, state and data flows, performance-sensitive experiences, and reliable testing patterns for consumer-scale products.
• Coordinate across frontend and backend boundaries by making the API or backend changes necessary to complete the product experience, rather than stopping at team interfaces.
• Maintain a high bar for AI-generated code through critical review and by leveraging automated tests, observability, staged rollouts, and rollback mechanisms to verify correctness.
• Improve the team’s AI-native engineering workflow by converting repetitive work into reusable agent workflows, tooling, conventions, and playbooks that increase delivery speed.
• Modernize existing systems by incrementally refactoring legacy frontend and service code so both engineers and AI agents can safely understand and modify it.
• Own production outcomes by investigating performance issues, regressions, and incidents using logs, metrics, experiments, and AI-assisted debugging.

Required Qualifications

• 3+ years of software engineering experience, with strong depth in frontend or client-side product engineering.
• Strong JavaScript/TypeScript fundamentals and hands-on experience with React or a comparable modern frontend framework.
• Experience shipping meaningful user-facing features in production and making frontend architecture decisions around components, state, data flow, performance, or testing.
• Evidence of working beyond the frontend layer, including designing or modifying APIs, backend services, data contracts, or developer tooling.
• Hands-on experience using modern AI coding tools or coding agents as part of real development work, not limited to occasional autocomplete.
• Solid engineering fundamentals with the ability to reason about system behavior, debugging, reliability, testing, and performance.
• Ability to learn unfamiliar technologies quickly and use AI effectively to expand into adjacent parts of the stack.
• Strong product mindset focused on user experience and business outcomes.
• Comfort working in a fast-moving environment where engineers help define solutions rather than only executing a detailed specification.

Technologies

• JavaScript
• TypeScript
• React
• Node.js
• Java
• Kotlin
• Python
• LLMs

Location and Compensation

• Location: Mountain View, CA (onsite)
• Salary: USD 118,000 - 212,000 per year

Bonus Points

• Experience building AI-native or agent-powered user experiences.
• Experience building or operating coding agents, LLM workflows, or developer productivity tools.
• Backend experience with Java, Kotlin, Python, Node.js, or similar technologies.
• Experience with recommendation, feed, search, ads, growth, or other large-scale consumer products.
• Experience improving web performance, experimentation infrastructure, design systems, or CI/CD quality gates.
• Experience shipping products in a small, highly autonomous team.