Principal Engineer, AI
About The Position
Brightwheel is the largest, fastest growing, and most loved platform in early education, trusted by millions of educators and families every day. We are a three-time Cloud 100 company, backed by top investors. Our team is passionate, talented, and customer-focused. We are a distributed team with remote employees across every US time zone, as well as select offices in the US and internationally. You are a Principal Engineer who is both AI-native and relentlessly product-minded. You turn ambiguous, cross-team opportunities into clear technical direction, and then you prove the path by building. You care about the flagship experiences you ship, and you obsess over the shared "paved highway" that makes it easy for the teams around you to ship safe, reliable AI over and over again.
Requirements
- Foundational AI Depth: You possess deep intuition for why models fail, gained from experience that predates the LLM boom. You have likely worked with model training, fine-tuning, or classical NLP/ML, giving you the grounding to make sound architectural decisions.
- 8+ Years of Engineering Excellence: You have end-to-end ownership of large, business-critical systems. You launch large-scale and/or highly complex software that requires members of multiple teams to contribute, and you deliver largely independently with minimal guidance.
- Architectural Strategy: Experience formulating architectural strategy at the organization level. You have designed systems that required execution across multiple teams, and you regularly influence technical and product priorities.
- Mentorship and Hiring: A track record of mentoring senior and staff engineers and improving their skills, knowledge, and ability to get things done. You actively interview engineers and your judgment carries weight in debriefs.
- Production AI at Scale: A proven track record of shipping AI-powered products to production. You understand the "last mile" of AI—evaluation, monitoring, and safety—and have built the tools that allow teams to sleep soundly at night.
Nice To Haves
- Experience earlier in your career with model training, fine-tuning, classical machine learning, or natural language processing—enough to have intuition for why models fail and how data and evaluation shape outcomes.
- A portfolio of real work (open-source, demos, writing, talks, or shipped side projects) that shows taste, velocity, and how you think about applied AI systems end-to-end.
- Experience building shared internal platforms or frameworks (for example evaluation services, retrieval infrastructure, policy and safety guardrails, observability tooling) that became the default path for multiple teams.
- Formal training in computer science (4-year CS degree or equivalent depth in core CS topics).
- A strong bar for operational excellence: secure-by-default design, performance and cost discipline, testability, incident readiness, and a track record of improving development, testing, and on-call practices for complex systems.
Responsibilities
- Own outcomes end-to-end. Take responsibility for turning high-leverage opportunities into shipped, adopted capabilities with clear measurement, iteration loops, and sustained improvement—not one-time launches.
- Define the AI technical direction for your organization. Translate customer problems into a practical strategy, reference architectures, and a roadmap that multiple teams can execute against, with minimal guidance.
- Drive build-versus-buy decisions. Recommend when to partner on models and tooling versus when to build differentiated capabilities (data flywheels, evaluation systems, workflow-specific intelligence), backed by evidence from fast, hands-on spikes.
- Lead by implementation. Rapidly prototype and ship reference implementations to prove feasibility, de-risk decisions, and raise your teams' expectation for speed and ambition.
- Help build the paved highway. Contribute shared foundations—evaluation harnesses, retrieval and context patterns, safety guardrails, observability, and developer experience—so teams can ship reliable AI features repeatedly and independently.
- Raise the bar across your organization. Mentor senior and staff engineers, lead design reviews for your teams, help establish standards for quality and safety, and align stakeholders to drive adoption.
Benefits
- We are committed to creating a diverse and inclusive work environment and are an equal opportunity employer.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Associate degree
