Instructor - AGS + Agentic AI
Fullstack Academy
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Job summary
Simplilearn is seeking an Online Trainer – AGS & Agentic AI to deliver engaging, industry-focused online training for adult learners.
You will facilitate live sessions on Advanced Generative AI, Agentic AI, AI agents, LLMs, RAG, and tool-using agents, connecting theory to business applications with hands-on labs.
This 100% online role requires hands-on expertise and strong instructional ability, with curriculums updated regularly to reflect emerging AI architectures.
Qualifications
- 8+ years in AI, Generative AI or related tech domains.
- Experience delivering online instructor-led training to professionals.
- Strong understanding of AGS/Agentic AI concepts and tools.
Responsibilities
- Deliver live online instructor-led training sessions on AI agents and agentic workflows.
- Cover topics: Advanced Generative AI, Agentic AI, LLMs, RAG, tool calling.
- Prepare labs, demonstrations, and real-world business case studies.
- Maintain high learner engagement and update content with new trends.
Skills
Education
Tools
Job description
About Us
Simplilearn is the world’s #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialised training offered in partnership with world‑renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, artificial intelligence, cybersecurity, product management, and more—skills that are transforming the global economy. Our training is hands‑on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2,000 corporate training organisations across 150 countries have harnessed our award‑winning programmes to achieve their career and business goals.
Simplilearn has collaborated with Fullstack Academy to leverage its widespread footprint in the US region and partnerships with top US universities to grow internationally.
The Online Trainer – AGS & Agentic AI will play a key role in delivering engaging, practical, and industry‑focused learning experiences to adult learners enrolled in our advanced Generative AI and Agentic AI programmes.
The trainer will facilitate live online training sessions covering Advanced Generative AI, Agentic AI, AI Agents, Large Language Models, Prompt Engineering, RAG, AI‑powered automation, multi‑agent systems, AI workflows, and LLM‑powered applications.
This role requires a strong combination of hands‑on technical expertise, industry experience, and instructional ability. The trainer will be responsible for explaining advanced AI concepts, demonstrating real‑world AI agent implementations, conducting hands‑on activities, and connecting technical concepts to practical business use cases.
The ideal candidate should have significant hands‑on experience designing, building, implementing, or deploying AI agents, agentic workflows, LLM‑powered applications, RAG systems, tool‑using agents, multi‑agent systems, and AI automation solutions.
Candidates should also be comfortable working with modern AI tools and frameworks, including ChatGPT, Claude, Gemini, LangChain, LangGraph, CrewAI, AutoGen, AI APIs, coding agents, and workflow automation platforms.
Classes are delivered 100% online in a synchronous, instructor‑led format.
Deliver live online instructor‑led training sessions covering Advanced Generative AI, Agentic AI, AI Agents, LLMs, AI automation, and emerging AI technologies.
Cover core AGS and Agentic AI topics including:
- Advanced Generative AI concepts and applications
- Evolution of Generative AI towards Agentic AI
- AI Agents and autonomous AI systems
- Agentic AI architectures and design patterns
- Agentic workflows and automation
- Large Language Models and LLM‑powered applications
- Prompt Engineering and advanced prompting techniques
- Context Engineering
- Retrieval‑Augmented Generation (RAG)
- Tool calling and function calling
- AI agent memory and context management
- Planning, reasoning, and task decomposition
- Multi‑agent systems and agent collaboration
- LLM orchestration
- AI‑powered workflow automation
- AI agents interacting with APIs, databases, files, and external tools
- Building end‑to‑end AI agent solutions
- Evaluating and improving AI agent performance
- Responsible AI, security, privacy, bias, and governance
- Emerging trends in Agentic AI and autonomous systems
Prepare and continuously update:
- Training presentations
- Learning materials
- Practical exercises
- Hands‑on labs
- Agentic AI demonstrations
- AI agent use cases
- Real‑world business case studies
- Prompt libraries and templates
- Reference architectures
- Practical assignments and activities
Conduct interactive workshops, Q&A sessions, knowledge checks, guided practice, and hands‑on demonstrations.
Conduct practical demonstrations using modern AI tools, platforms, frameworks, and development environments such as:
- ChatGPT
- Claude
- Gemini
- Microsoft Copilot
- LangChain
- LangGraph
- CrewAI
- AutoGen
- AI APIs and LLM platforms
- RAG frameworks
- Vector databases
- Embedding and retrieval technologies
- n8n and other workflow automation platforms
- AI coding agents and development tools
- Python and AI development environments
Demonstrate how AI agents can:
- Understand and decompose complex tasks
- Plan and reason through multi‑step problems
- Use tools and external APIs
- Retrieve and analyse information
- Maintain context and memory
- Collaborate with other specialised agents
- Execute automated workflows
- Interact with enterprise systems
- Generate and validate outputs
- Operate with human‑in‑the‑loop oversight
Guide learners through real‑world Agentic AI scenarios across business functions such as operations, marketing, finance, customer service, software development, research, productivity, and enterprise automation.
Support learners in designing and developing practical LLM‑powered applications, AI agents, multi‑agent systems, RAG applications, and AI automation workflows.
Maintain high learner engagement and instructional quality throughout all sessions.
Stay current with rapidly evolving Generative AI, Agentic AI, AI agent frameworks, LLMs, AI coding agents, automation platforms, and emerging AI architectures.
Collaborate with internal curriculum teams to continuously improve training content, practical activities, and learner outcomes.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 8+ years of professional experience in Artificial Intelligence, Generative AI, Machine Learning, Software Engineering, Data Science, or related technology domains.
- Significant hands‑on experience with Generative AI and Agentic AI technologies.
- Demonstrated experience designing, developing, implementing, or deploying AI agents or LLM‑powered applications.
- Prior experience delivering online instructor‑led training to professionals or adult learners.
- Strong understanding of Generative AI, LLMs, Agentic AI, AI agents, automation, and AI‑powered applications.
- Strong understanding of:
- Agentic AI architectures
- AI agent design and development
- LLM‑powered applications
- Agentic workflows
- Prompt Engineering
- Context Engineering
- Retrieval‑Augmented Generation (RAG)
- Tool calling and function calling
- Agent memory and context management
- Planning and reasoning
- Task decomposition
- Multi‑agent systems
- LLM orchestration
- AI workflow automation
- AI APIs and integrations
- Responsible AI, security, privacy, and governance
- Hands‑on experience with Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
- Strong experience working with modern LLM platforms such as OpenAI, Anthropic, Google Gemini, Microsoft Copilot, or similar platforms.
- Strong understanding of AI automation and workflow orchestration.
- Experience with Python or another programming language used for AI development.
- Excellent communication, presentation, storytelling, and facilitation skills.
- Strong hands‑on expertise in Generative AI and Agentic AI.
- Strong practical experience building or implementing AI agents and agentic workflows.
- Ability to simplify advanced AI concepts through practical examples and live demonstrations.
- Experience building or demonstrating LLM‑powered applications, RAG solutions, AI agents, and automation workflows.
- Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar Agentic AI frameworks.
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