AI Product Engineer

Blackboard

1d•Remote

About The Position

We're a small team within Blackboard building a new AI-native product. This is not a feature team, and it's not an enhancement to an existing product — we're building something new. 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. On a team this small, there are no handoffs. The person who designs a feature ships it. The person who builds the data pipeline also builds the product surface that consumes it. We're looking for builders who are energized by that scope, not overwhelmed by it. 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.

Requirements

Work natively with AI coding tools (Cursor, Claude Code, or equivalent) — not as a curiosity, but as your actual development workflow
Shipped products to real users — full-stack, with real accountability for whether they work
Comfortable across the stack: React/Next.js/TypeScript on the frontend, Node.js or Python on the backend, PostgreSQL for data
Integrated LLM APIs or built AI-powered features in production (streaming, structured outputs, agent patterns)
Strong product instincts: notice when something feels off in the user experience and fix it, even if it wasn't in your ticket
Ability to move fast, make good decisions under ambiguity, and leave the codebase better than you found it
Fluency in written and spoken English

Nice To Haves

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

Responsibilities

Design and ship student-facing product interfaces, focusing on the core user experience that learners interact with daily
Build real-time features that surface AI intelligence in ways that feel immediate and useful, not mechanical
Develop responsive, performant UI built on a shared component library
Create API routes and backend services connecting the user interface to the intelligence and data layers
Integrate AI orchestration: streaming responses, agent outputs, structured recommendations in context
Develop event-driven ingestion pipelines that translate platform activity into structured, reliable signals
Design storage architecture and schema for persistent user state — built to evolve as the product grows
Manage deployment infrastructure, CI/CD, and environment
Implement data access controls and audit logging that satisfy institutional security and compliance requirements
Own end-to-end features from spec to production — including testing, monitoring, and iteration
Actively use AI-assisted development tooling to maintain high output without sacrificing code quality
Contribute 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.