Staff AI Product Builder

Role Overview

As a Staff AI Product Builder (full remote), you’ll drive AI-powered improvements across Brightwheel’s core workflows. You’ll design and build cross-cutting AI services, shape data and system architecture, and lead AI-augmented engineering that ships reliably in production.

Key Missions

• Own AI-powered improvements in core workflows, from opportunity sizing to launch and iteration.
• Design and build cross-cutting AI services that support multiple product areas with consistency and reliability.
• Lead by example in AI-augmented engineering: mentor engineers, and raise the bar for how AI features are designed, shipped, and operated.

Responsibilities (What you’ll do)

• Build and iterate on AI features that improve real-world metrics (e.g., engagement, time saved, satisfaction, retention).
• Work across backend, data, and UX to deliver end-to-end AI-enabled product outcomes.
• Contribute to platform capabilities adopted by multiple teams.
• Raise engineering quality through strong practices in security, testing, maintainability, and operational excellence.

Requirements

• Backend engineering skills in at least one modern web stack (e.g., Ruby on Rails, Python, Go, or Node), with strong relational database confidence (data modeling, performant queries, analytics).
• Strong computer science fundamentals and systems design skills; generalist mindset.
• Shipped AI-powered products to production with evidence that LLMs improved metrics.
• Hands-on LLM experience in real applications, including:
  • Prompt and tool design
  • Retrieval-style patterns (e.g., RAG)
  • Evaluation and monitoring in production
• Experience with modern web front-ends, ideally React.
• 5+ years professional software engineering experience with ownership of medium-to-large production systems end-to-end (problem statement/design docs through launch/iteration).
• Track record of raising quality and operations: secure, testable, maintainable code, automation for dev/test/ops workflows, design docs, mentorship, and interview contributions.
• Experience designing shared platforms/frameworks used by multiple teams (e.g., internal SDKs, evaluation services, experimentation tooling).
• Background in operations-heavy domains like vertical SaaS or ecommerce.
• Portfolio of personal AI projects/open-source/writing demonstrating applied AI thinking.
• Formal CS training (4-year degree or equivalent depth).

Nice-to-Haves

• Experience specifically with AI evaluation/monitoring platforms and experimentation tooling.
• A history of cross-functional AI delivery touching backend, data, and UX.