• We're a small team within Blackboard building a new AI-native product. • AI coding tools — Claude Code, Cursor, and similar — generate the majority of our code. • Our engineers are architects, reviewers, and product thinkers: people who know how to direct AI development agents effectively, ship features end-to-end and make judgment calls when the requirements are still evolving. • Everyone on the engineering team owns features end-to-end — from the data pipeline to the AI orchestration layer to the student-facing interface. • The work varies by the week, and the surface area is large. • Real-time features that surface AI intelligence in ways that feel immediate and useful, not mechanical. • Responsive, performant UI built on a shared component library. • Deployment infrastructure, CI/CD, and environment management — no dedicated DevOps to hand off to. • Contribution to shared component libraries and codebase standards as the team grows. • Active use of AI-assisted development tooling to maintain high output without sacrificing code quality. • Stay on the bleeding edge of the AI ecosystem — Claude Code, Cursor, OpenAI Agent SDK, MCPs, and whatever comes next.