About The Position

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 an AI-native Director of Engineering who combines exceptional engineering judgment, product sense, and high standards with the ability to scale leaders, teams, and execution. You create clarity in ambiguous spaces, turn company priorities into high-velocity delivery, and lead by example in how modern engineering gets done. You care deeply about the CX your team ships, and you help make AI-native execution practical, repeatable, and fast across the organization. You will succeed in this role if you are: Focused on business impact. You care about scaling brightwheel’s value and impact by orders of magnitude. You treat technology as a driver of growth and operational efficiency, always connecting engineering decisions to better outcomes for educators, administrators, and families. A practitioner-leader. You do not lead from a distance. You use AI agents and modern tooling in your own work to raise the organization’s ambition, show what great looks like, and help teams adopt better ways of building. What You’ll Do brightwheel already supports the workflows that keep early education businesses running: enrollment, billing, staffing, classroom operations, family communication, and compliance. The next step is bigger. We can use AI to turn brightwheel from a system of record into a system of action, reducing toil, automating routine work, improving decision-making, and accelerating how we build. You will turn that opportunity into reality. You will build teams, systems, and AI-native ways of working that help brightwheel deliver more value to customers, move faster as an organization, and continuously raise the bar on product quality, reliability, and execution.

Requirements

  • A strong computer science foundation. You have a 4-year computer science degree or equivalent depth in core computer science topics, with the technical grounding to reason well across systems, abstractions, and tradeoffs.
  • A record of shipping battle-tested products at scale. You have helped deliver customer-facing software from pixels to metal, in either consumer or enterprise software. You have seen what it takes to make products succeed in real production environments with real customers and business stakes.
  • Applied AI experience in production. You have used AI, automation, or machine learning in high-stakes environments, whether in customer-facing products, internal systems, or engineering workflows. You understand what it takes to make these systems useful, reliable, safe, and cost-effective.
  • Experience leading through leaders. You have managed managers and senior engineers, building teams that consistently delivered meaningful product or platform outcomes in demanding, fast-paced environments.

Nice To Haves

  • Product taste and judgment. You operate without needing a product manager crutch. You are excited by the challenge of defining the right thing to build, not just building it right. In the age of AI, you use your product intuition to bridge the gap between technical possibility and customer value.
  • High-stakes communication and influence. You are equally comfortable in the boardroom and the IDE. You can persuade a C-suite audience on high-stakes strategic bets while maintaining the deep technical respect of the engineers who are building the systems.
  • A proven talent magnet. You have a track record of building or turning around teams in highly competitive hiring arenas. You have successfully attracted and retained top talent.
  • You are a T-shaped leader, deeply expert in at least one domain but capable of becoming proficient just-in-time across science, data, security, infra, and UX. You use AI to multiply your learning speed, allowing you to handle the full breadth of a modern engineering organization.
  • Hands-on fluency with AI-native development. You do not just manage; you build. You have used AI assistants and agents to materially improve your own speed and quality, and you have a clear perspective on how to help an entire organization adopt these workflows effectively.

Responsibilities

  • Lead engineering teams that deliver AI-powered product and platform capabilities with clear impact. Reduce administrative toil, improve family responsiveness, streamline enrollment, and surface better insights for operators.
  • Build software that not only records information, but also recommends next steps, completes routine work, and automates meaningful parts of our customers’ day-to-day operations.
  • Use AI agents, automation, and modern tooling to improve how teams build, test, ship, and support software, increasing velocity and freeing up more capacity for high-value work.
  • Operate an AI hybrid engineering workforce in which engineers and agents work together effectively, with the tooling, guardrails, governance, evaluation, and observability required.
  • Apply the same AI-native mindset to internal functions like customer support and onboarding, helping the company become faster, more responsive, and more efficient as it scales.
  • Drive continuous improvements in quality, reliability, and security by using agentic workflows to catch issues earlier, reduce operational burden, and improve the product every week.
  • Hire and scale exceptional AI-native engineering talent, building a lean, high-performing organization with high standards, strong ownership, and a bias for action.
  • Make strong build-versus-buy, architecture, and platform decisions that balance short-term speed with long-term leverage and differentiation.
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