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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. 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.
Job Responsibility:
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
Requirements:
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 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 have:
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
What we offer:
Comprehensive medical, dental, and vision coverage
Generous paid parental leave
Flexible PTO so you can recharge when you need it
Local retirement or savings plans (e.g., 401(k) in the U.S.)