Lead Instructor: AI-Enabled Product Manager

General Assembly

12h•Remote

About The Position

General Assembly is delivering an intensive reskilling program designed to transition Customer Success and Account Management professionals into AI-powered product management roles. As the Lead Instructor, you will move beyond high-level validation to direct delivery. You will be responsible for guiding experienced professionals through the practical application of AI in product management, ensuring they can effectively discover, prioritize, and scope AI-driven features in a real-world business context.

Requirements

7+ years in product management with at least 2+ years of hands-on experience shipping AI-powered features in a production environment.
Proven experience teaching or mentoring professionals, with the ability to simplify complex AI concepts for a non-engineering audience.
Deep familiarity with AI product discovery frameworks and the ability to apply standard PM metrics (OKRs, JTBD) specifically to AI-driven initiatives.
Working knowledge of the Microsoft ecosystem, including Copilot and Azure AI Foundry.

Nice To Haves

AI-900 or AI-102 certification is a significant plus.
Experience as a PM or GPM at a major tech firm like Microsoft or Google is strongly preferred.

Responsibilities

Lead Synchronous Instruction: Deliver live, high-impact remote lectures on AI product discovery frameworks, including Jobs-to-be-Done (JTBD) and OKRs applied to AI features.
Facilitate Interactive Sessions: Lead "prompt-along" sessions and guide students through hands-on, self-paced exercises to ensure technical and conceptual mastery.
Guide Product Strategy: Help learners navigate the nuances of AI roadmapping, product prioritization, and the internal/external positioning of LLM-powered products.
Technical Mentorship: Provide expert guidance on using the Microsoft product suite, specifically Copilot and Azure AI Foundry, within the product management lifecycle.
Direct Learner Feedback: Evaluate student progress and provide actionable feedback on their ability to scope and define AI-enabled product features.