Live opening · Posted 19 days ago

Technical Trainer - Agentic AI

AIM · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 19 days ago
CompanyAIM
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SourceLinkedin
Listed19 days ago

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About the role

Description supplied by the original job listing.

We are seeking an experienced Learning Consultant in Agentic AI and Enterprise AI to design and deliver advanced corporate training programs for enterprise professionals, architects, technical leads, and AI transformation teams.
Key Responsibilities
Deliver enterprise workshops on Agentic AI, MCP, A2A, RAG, AI orchestration, AI governance, and enterprise GenAI.
Design hands-on labs, simulations, capstones, architecture exercises, and enterprise AI workshops.
Create e-learning assets including recorded videos, assignments, assessments, facilitator guides, and learning content.
Customize programs for enterprise clients across BFSI, Manufacturing, Retail, Healthcare, GCCs, and IT Services.
Support capability-building initiatives, client workshops, and AI transformation programs.
Required Experience
8+ years of experience in Agentic AI, ML, data engineering, cloud, or enterprise architecture domains. Agentic AI experience like A2A, MCP, & RAG is mandatory
Strong B2B corporate training experience for mid-level and senior professionals.
Experience designing enterprise learning journeys and workshop-led learning programs.
Should not be limited to fresher/B2C-only training experience.
Should not be limited to data science and Machine learning training. Skills with stacks like matplotlib, scikit learn, pandas, numpy would not qualify. We are looking for Agentic AI skills.
Technical Skills
Hands-on expertise in MCP, A2A, multi-agent systems, RAG, AI orchestration, and enterprise AI workflows. (mandatory)
Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, and vector databases. (mandatory)
Strong knowledge of AWS, Azure, or GCP AI ecosystems and cloud-native AI architectures. (Any one)
Experience with MLOps / LLMOps, observability, governance, APIs, microservices, and scalable enterprise systems. (good to have)
Preferred Profile
Excellent communication, facilitation, and instructional design skills.
Experience with blended learning models (ILT, VILT, self-paced).
Ability to engage architects, managers, delivery leaders, and enterprise stakeholders.
Experience with hackathons, innovation labs, or enterprise AI capability programs is preferred. (Optional)

Work arrangement
No

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