Great Learning - Manager - GenAI/Agentic AI Specialist - Enterprise Learning & Products

About the Role :

We are looking for a GenAI/Agentic AI Specialist to help us build and position next-generation upskilling products for enterprise clients. This is a hybrid role at the intersection of AI, product development, and enterprise learning - ideal for someone who is equally comfortable thinking about pedagogy, building with AI tools, and engaging with senior client stakeholders.

What You Will Do :

- Design and develop role-based GenAI and Agentic AI learning programs, translating complex AI concepts into practical, workflow-embedded curricula for enterprise professionals

- Build reusable learning assets that participants can directly apply in their roles

- Develop product demonstrations, POCs, and sample use cases that showcase our capabilities to enterprise clients during the pre-sales and solutioning phase

- Contribute to proposal development and client presentations, helping position our GenAI learning products effectively

- Design and facilitate gamified experiences that drive hands-on learning

- Stay current with the evolving GenAI/Agentic AI landscape - including tools, platforms, certifications, and enterprise adoption trends - and feed this into our product roadmap

- Work closely with internal teams and client stakeholders to customize programs based on specific organizational needs

What We Are Looking For :

- Experience : 3-4 years into techno-functional role with strong hands-on experience working with GenAI tools and platforms - including LLMs, agent frameworks, and workflow automation

- Understanding of enterprise learning and upskilling - experience designing or delivering training programs is a plus

- Ability to build working prototypes and demos, not just decks

- Strong communication and storytelling skills - able to translate technical capability into compelling client-facing narratives

- Experience working with or selling to large enterprises is an advantage

- MBA from Tier 1 B-schools will be preferred