Remote

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 and infrastructure that enable the broader engineering team to build safely and consistently.

• 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.
• Own the end-to-end product loop as a hybrid PM+Eng+Data builder: talk to customers and internal teams, define success metrics, design workflows and user experiences, shape data and evaluation plans, and ship iterative releases from prototype to reliable, scalable production.
• Create shared abstractions and tooling for AI - including 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., We work with:
• Backend: Ruby on Rails, Sidekiq
• Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines
• Frontend: React with TypeScript and Emotion
• Mobile: Native iOS (Swift) and Android (Kotlin with Jetpack Compose)
• Cloud & Infrastructure: Docker, Kubernetes on Amazon EKS, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, CloudWatch, and SNS
• AI & Automation: AWS Bedrock and other hosted large language models, vector search, orchestration and agent frameworks, and modern AI coding tools like Cursor

• 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 metrics like engagement, time saved, satisfaction, or retention.
• 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 structures, algorithms, and systems design) and a generalist mindset, comfortable moving between backend, data, and UX to get the job done.
• Backend engineering skills in at least one modern web stack (such as Ruby on Rails, Python, Go, or Node), plus confidence with relational databases and larger datasets, from data modeling to performant queries and analytics.
• Experience building modern web front-ends, ideally with React or a similar component-based framework.

Nice-to-haves:

• Formal training in computer science (4-year CS degree or equivalent depth in core CS topics).
• A portfolio of personal AI projects, open-source work, or writing that shows how you think about applied AI in real-world settings.
• Background in vertical SaaS, ecommerce, or other operations-heavy domains.
• Experience designing shared platforms or frameworks (for example, internal SDKs, evaluation services, or experimentation tooling) adopted by multiple teams.
• A track record of raising the bar for quality and operations: writing secure, testable, maintainable code; automating and simplifying dev/test/ops workflows; writing and reviewing design docs; mentoring other engineers; and contributing to hiring through interviews and feedback.

Lead end-to-end development of AI-powered features and shared AI services, own product loop from discovery to production, design data and system architecture, create reusable tooling and guardrails, mentor engineers, and ensure secure handling of sensitive school and family data. The summary above was generated by AI Our Mission and Opportunity Early education is one of the most important determinants of childhood outcomes, a critical support for working families, and a $175B market that remains underserved by modern technology. Brightwheel is the largest, fastest growing, and most loved platform in early ed, trusted by millions of educators and families every day. We are a three-time Cloud 100 company, backed by top investors including Addition, Bessemer, Emerson Collective, Lowercase Capital, Notable Capital, and Mark Cuban. 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. 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." You focus on measurable user and business impact. * AI-native. You treat AI as part of your toolchain: you rely on modern AI coding assistants and lightweight automation or orchestration tools to move dramatically faster, and you know when AI adds real leverage versus when a simpler approach is sufficient. * 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 users interact with - while also 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.