Staff AI Product Builder

Headquarters: United States Our Mission and Opportunity Early education is one of the greatest determinants of childhood outcomes, is a must for working families, and has lasting social and economic impact. Brightwheel's vision is high quality early education for every child. We pursue this by directly supporting teachers in the classroom, engaging parents in the development of their kids, and enabling the small businesses that make up the backbone of the $175 billion early education industry. Brightwheel is the most loved technology brand in early education, trusted by tens of thousands of providers and millions of educators and families. Our Team Our team is passionate, talented, and customer-focused. We embody our Leadership Principles in our work and culture. We are a distributed team with remote employees across every US time zone, as well as select offices in the US and internationally. Our exceptional investor group includes Addition, Bessemer, Emerson Collective, Lowercase Capital, Mark Cuban, Notable Capital, and others. Who You Are You are a Staff level full-stack builder who is both AI-native and product-minded. You love taking an ambiguous customer problem, turning it into a clear plan, and shipping a real end-to-end experience that moves a meaningful outcome. You care about craft and trust in what you ship, and you leave behind reusable building blocks so the next team can move even faster. You will succeed in this role if you are: • Driven by outcomes. You care about helping preschools and childcare centers stay full, save time, and serve families better – not just about shipping "an AI feature." • AI-native. You treat AI as part of your toolchain: you rely on modern AI coding assistants and IDEs and lightweight automation or orchestration tools to move dramatically faster, and you know when AI adds real leverage versus when a simple service or query is enough. • A product-driving technical leader. You don't wait for perfect requirements — you validate hypotheses with prototypes, talk to customers and internal teams, define success metrics, and use working software to align others and drive decisions. • Full stack with a platform mindset. You are comfortable designing data models and APIs, implementing backend logic, and building the front-end experiences that sit on top – and you enjoy creating shared services and patterns that other teams can reuse. • Thoughtful about AI's limits. You understand hallucinations, safety, and evaluation, and you design data flows, UX, and guardrails around those constraints rather than ignoring them. • Security-minded. You handle sensitive school, educator, and family data with care and instinctively look for secure designs and least-privilege access patterns. What You'll Do In this role, you'll own AI-powered improvements in core brightwheel workflows end-to-end, from opportunity sizing to launch to iteration. You'll ship experiences that make administrators and teachers faster and more effective, while creating shared patterns that help the rest of engineering build safely and consistently. You will: • Design and build cross-cutting AI services (such as retrieval, context, evaluation, and guardrails) that power multiple product areas like classroom workflows, billing, and family communication. • As a hybrid PM+Eng+Data builder: own the end-to-end product loop for the problems you take on: talk to customers and internal teams, define the success metric, design the workflow and user experience, shape the data and evaluation plan, and ship iterative releases from prototype to reliable, scalable production. • Create shared abstractions and tooling for AI – for example, common prompt and tool patterns, logging and monitoring, and reusable components – so other engineers can build on a consistent foundation. • Shape our data and system architecture so AI can safely stitch together longitudinal signals across product, billing, support, and operations and recommend what should happen next, not just report what happened. • Lead by example in AI-augmented engineering, using AI to multiply your own speed, mentoring L2/L3 engineers, and raising the bar for how we design, ship, and operate AI-powered features. What You've Done We are open to a variety of backgrounds, but you likely bring: • 5+ years of professional software engineering experience, with clear ownership of medium-to-large production systems from problem statement and design doc through launch and iteration. • A proven track record of shipping AI-powered products to production, with concrete examples where LLMs meaningfully improved a metric like engagement, time saved, satisfaction, or retention across one or more product areas. • Hands-on experience with large language models (LLMs) in real applications, including prompt and tool design, retrieval-style patterns (such as RAG), and evaluation and monitoring in production. • Strong computer science fundamentals (e.g., data structure