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

About NewsBreak Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech. Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale. Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about AI Engineer — AI-Native Product Engineering Location: Mountain View, CA About the Team 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. What You’ll Do 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…