AI Product Engineer

Blackboard is a company focused on advancing teaching excellence through technology. They are seeking an AI Product Engineer to build a new AI-native product, where the engineer will own features end-to-end, from design to production, and integrate various AI and backend components.

Responsibilities:

• Student-facing product interfaces — the core user experience that learners interact with daily
• 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
• API routes and backend services connecting the user interface to the intelligence and data layers
• AI orchestration integration: streaming responses, agent outputs, structured recommendations in context
• Event-driven ingestion pipelines that translate platform activity into structured, reliable signals
• Storage architecture and schema design for persistent user state — built to evolve as the product grows
• Deployment infrastructure, CI/CD, and environment management — no dedicated DevOps to hand off to
• Data access controls and audit logging that satisfy institutional security and compliance requirements
• End-to-end feature ownership from spec to production — including testing, monitoring, and iteration
• Active use of AI-assisted development tooling to maintain high output without sacrificing code quality
• Contribution to shared component libraries and codebase standards as the team grows
• Stay on the bleeding edge of the AI ecosystem — Claude Code, Cursor, OpenAI Agent SDK, MCPs, and whatever comes next. When a better way to build exists, find it and bring it in

Requirements:

• You work natively with AI coding tools (Cursor, Claude Code, or equivalent) — not as a curiosity, but as your actual development workflow
• You've shipped products to real users — full-stack, with real accountability for whether they work
• You're comfortable across the stack: React/Next.js/TypeScript on the frontend, Node.js or Python on the backend, PostgreSQL for data
• You've integrated LLM APIs or built AI-powered features in production (streaming, structured outputs, agent patterns)
• Strong product instincts: you notice when something feels off in the user experience and you fix it, even if it wasn't in your ticket
• You can move fast, make good decisions under ambiguity, and leave the codebase better than you found it
• Fluency in written and spoken English
• Experience with event-driven data pipelines, vector stores, or RAG pipeline design
• Familiarity with infrastructure and deployment (CI/CD, managed services, observability tooling)
• Background in consumer-facing products where user behavior and engagement genuinely matter