Since 2011, General Assembly has transformed tens of thousands of careers through pioneering, experiential education in today’s most in-demand skills. As featured in The Economist, Wired, and The New York Times, GA offers training in web development, data, design, business, and more, both online and at campuses around the world. Our global professional community boasts 60,000 full- and part-time alumni — and counting. In addition to fostering career growth for individuals, GA helps employers cultivate top tech talent and spur innovation by transforming their teams through strategic learning. More than 21,000 employees at elite companies worldwide have honed their digital fluency with our upskilling and reskilling initiatives. GA has also been recognized as one of Deloitte’s Technology Fast 500, and Fast Company has dubbed us leaders in World-Changing Ideas as well as the #1 Most Innovative Company in Education.

GA is at the leading edge of creating practical solutions to one of the most pressing challenges of our time - the future of work. As recognized by The World Economic Forum, BCG, the OECD and more, these are big challenges to which only a few companies are offering real solutions. In this role, you'll be speaking every day to corporate leaders who rely on GA to help them apply these solutions to their workforce of the future.

Job Title: Lead Instructor: Agentic AI Engineering

Company:General Assembly

Client: Confidential – Customer Success Reskilling

Location: Remote (Must work West Coast / Pacific Time hours)

Duration: 2 Weeks (Starting Mid-June)

Commitment: Roughly 30 hours per week

Compensation: $11,500 - $15,500 (Estimated lump sum payment for one 60-hour program)

About the Engagement

General Assembly is delivering an intensive reskilling program designed to transition experienced Customer Success and Account Management (CSAM) professionals into technical roles focused on Agentic AI Engineering.

As the Lead Instructor, you will lead the charge in teaching students how to design and build sophisticated multi-agent systems. You will move beyond theory to help learners master tool use, memory, and long-horizon planning. This is a high-impact, 2-week "sprint" where you will be the primary technical guide for a cohort of professionals entering the world of autonomous AI orchestration.

What You’ll Do

Lead Live Technical Instruction: Deliver synchronous remote lectures and "build-along" sessions focused on designing agentic systems within Azure AI Foundry, Copilot Studio, and Semantic Kernel.
Facilitate Complex Labs: Guide students through hands-on exercises involving agent design patterns, multi-agent orchestration, and API integration.
Code Mentorship: Provide real-time troubleshooting and debugging support in Python as students build out their labs and capstone projects.
Translate Architecture: Break down complex systems-thinking and architecture concepts—such as memory management and planning in LLMs—into actionable steps for non-engineering professionals.
Office Hours & Feedback: Hold dedicated sessions to review student builds, ensuring their agentic systems are robust, scalable, and technically sound.

What You Bring

The Expertise: 7+ years in software engineering, with at least 2+ years of hands-on experience building and deploying agentic AI systems in a production environment.
The Tech Stack: Deep proficiency in Azure AI Foundry, Copilot Studio, and Semantic Kernel. (Experience with LangChain or LangGraph is highly valued as an adjacent skill set).
Core Skills: Expert-level Python proficiency, API design, and advanced prompt engineering. You should have a deep understanding of agent design patterns (tool use, planning, and orchestration).
Instructional Presence: Proven experience teaching technical topics or leading engineering teams. You must be comfortable engaging a remote audience and managing a fast-paced learning environment.
The Credentials: AZ-900 and AI-900 are required; AI-102 is strongly preferred.
Preferred Background: Experience as an AI Engineer or Azure S

Lead Instructor: Agentic AI Engineering at General Assembly