AI Engineer — AI-Native Product Engineering(frontend focus)

About NewsBreak

Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what’s going on in their zip code.

Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn.

Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We’re Great Place to Work® certified and named to Fast Company’s Best Workplaces for Innovators (2025) and Fortune’s Best Workplaces in the Bay Area™ (2026).

Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us.

Learn more at: NewsBreak, Nearby AI, NDot AI

Location: Mountain View, CA

We are rethinking how software is built in an AI-native world.

AI is becoming the default way we design, build, test, debug, and operate software. Engineers on this team work with coding agents to ship production products quickly, while setting the architecture, context, quality standards, and guardrails that make AI-generated software reliable.

This role is frontend-leaning, but not frontend-limited. We are moving away from traditional frontend/backend boundaries. You will start from strong client-side product engineering skills and use AI to work effectively across APIs, backend services, data flows, and developer tooling.

The expectation is simple: own the problem end to end, not just one layer of the stack.

• Build user-facing products end to end. Own features from product requirements and frontend architecture through API integration, backend changes, testing, rollout, and production metrics.
• Use AI as a core development tool. Work with coding agents to generate, refactor, test, debug, and understand code, while providing the context and validation needed for production quality.
• Own frontend architecture and product quality. Build maintainable component systems, state and data flows, performance-sensitive experiences, and reliable testing patterns for consumer-scale products.
• Cross frontend/backend boundaries. Make the API or backend changes needed to complete a product experience rather than handing work off at team boundaries.
• Set a high bar for AI-generated code. Review outputs critically and use automated tests, observability, staged rollout, and rollback mechanisms to verify correctness.
• Improve the AI-native engineering workflow. Turn repetitive development work into reusable agent workflows, tooling, conventions, and playbooks that make the team faster.
• Modernize existing systems. Refactor legacy frontend and service code incrementally so both engineers and AI agents can understand and modify it safely.
• Own production outcomes. Investigate performance issues, regressions, and incidents using logs, metrics, experiments, and AI-assisted debugging.

• 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 that you can work beyond the frontend layer — for example, designing or modifying APIs, backend services, data contracts, or developer tooling.
• Hands-on use of modern AI coding tools or coding agents as part of real development work, not only occasional autocomplete.
• Strong engineering fundamentals and 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: you care about user experience and business outcomes, not just implementation.
• Comfortable operating in a fast-moving environment where engineers help define the solution rather than simply execute a detailed specification.

• 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 0→1 products in a small, highly autonomous team.

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