Staff AI Product Builder, Data Engineering
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Responsibilities
- In this role, you will own AI-powered improvements in core brightwheel workflows end-to-end, with particular emphasis on the data foundation that enables those workflows. You will:
- Ship "virtual employee" workflows that do real work before humans engage: research, verification, prioritization, deduplication, and prep artifacts that cite evidence and flag unknowns.
- Build a durable job execution system for agent workflows: retries, explicit budgets, idempotency, and monitoring.
- Create shared abstractions for AI and data systems: tool interfaces, logging, cost tracking, evaluation harnesses, data contracts, SLAs, and reusable workflow components that increase trust in both data and AI outputs.
- Partner with internal teams as customers. Define success metrics with them, design workflow delivery surfaces, and iterate based on adoption and impact.
- Lead by example in AI-augmented engineering, using AI tools to increase velocity while maintaining architectural rigor.
- What You've Done
- We are open to a variety of backgrounds, but you likely bring:
- 5+ years of professional engineering experience with clear ownership of production systems from design doc through launch and iteration.
- A track record of shipping AI-powered workflows to production with measurable impact, including hands-on experience with LLM tool use, retrieval patterns, evaluation, and monitoring.
- Experience operating AI systems in production: evaluation harnesses, rollout strategies, and monitoring that ties system health to output quality.
- Experience designing data platforms for operational use cases: canonical models, identity resolution and deduplication, and governance patterns that support safe downstream consumption.
- Experience designing reliable workflow systems: job orchestration, backfills and retries, observability, and cost/performance tradeoffs.
- Demonstrated ability to influence technical strategy across organizational boundaries.
Requirements
- You'll succeed in this role if you are:
- AI-native . You understand how LLMs interpret data and design retrieval, evaluation, and observability into systems from the start.
- A product-driving technical leader . You define what data should exist, how it should be structured, and how AI should safely interact with it to drive workflow improvements.
- Deep in data modeling and system design . You design schemas, contracts, and storage strategies that enable AI reasoning across domains, not just analytics queries.
- Thoughtful about safety and privacy . You build AI-aware data systems with governance, access control, and auditability as first-class concerns.
- Lakehouse or warehouse architectures that support both analytics and AI workloads.
- Vector indexing, embedding pipelines, or hybrid structured + semantic retrieval in production.
- Event-driven or real-time data architectures for operational intelligence, not just batch reporting.
- Vertical SaaS, CRM, or operations-heavy domains where operational da
Benefits
Additional Information
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.
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Company Intel
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