Instructor - Agentic AI

Key Responsibilities

• Deliver live online instructor-led training sessions covering Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, and Large Language Models.
• Cover core Agentic AI and Generative AI topics including:
• Agentic AI fundamentals and evolution
• AI Agents and autonomous AI systems
• Agent architectures and agentic workflows
• Large Language Models and LLM-powered applications
• Prompt Engineering and advanced prompting techniques
• 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
• AI workflow automation
• LLM orchestration
• Machine Learning and Deep Learning fundamentals
• Neural Networks, Attention Mechanisms, and Transformers
• Natural Language Processing and text classification
• BERT, GPT, GANs, VAEs, and Diffusion Models
• Responsible AI, security, bias, and ethical considerations
• Emerging trends in Agentic AI and autonomous AI systems
• Prepare and continuously update:
• Training presentations
• Learning materials
• Practical exercises
• Hands-on activities
• Agentic AI demonstrations
• AI agent use cases
• Real-world business case studies
• Templates and reference materials
• Conduct interactive workshops, Q&A sessions, quick knowledge checks, guided practice, and hands-on demonstrations.
• Conduct practical demonstrations using modern AI frameworks, platforms, and tools such as:
• LangChain
• LangGraph
• CrewAI
• AutoGen
• ChatGPT
• Hugging Face
• AI APIs and LLM platforms
• RAG frameworks and vector databases
• Workflow automation platforms
• Guide learners through real-world Agentic AI scenarios using practical business and industry examples.
• Demonstrate how AI agents can be designed to reason, plan, use tools, retrieve information, collaborate with other agents, and automate multi-step workflows.
• Support learners in developing practical skills for building and implementing LLM-powered applications and Agentic AI solutions.
• Maintain high learner engagement and instructional quality throughout all sessions.
• Stay updated with current Agentic AI practices, Generative AI developments, LLM technologies, AI frameworks, autonomous AI systems, and emerging industry trends.
• Collaborate with internal curriculum teams to continuously improve training content and learner outcomes.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related field.
• 10+ years of professional experience in Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, or related domains.
• Strong hands-on experience designing, developing, implementing, or deploying Agentic AI systems and LLM-powered applications .
• Prior experience delivering online instructor-led training for professionals or adult learners.
• Demonstrated expertise across AI, Machine Learning, Deep Learning, NLP, Generative AI, and Agentic AI.
• Strong understanding of:
• Agentic AI architectures and AI agents
• LLM-powered applications
• Agentic workflows and automation
• Large Language Models
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Tool calling and function calling
• AI agent memory and context management
• Planning, reasoning, and task decomposition
• Multi-agent systems
• LLM orchestration
• Machine Learning and Deep Learning
• Neural Networks, Attention Mechanisms, and Transformers
• NLP and text classification
• BERT, GPT, GANs, VAEs, and Diffusion Models
• Responsible AI, security, bias, and ethical AI
• Hands-on experience with Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks .
• Strong understanding of AI APIs, LLM integration, and AI automation workflows.
• Excellent communication, presentation, and facilitation skills.

Required Skills

• Strong hands-on expertise in Agentic AI and AI Agent development .
• Strong instructional and learner engagement abilities.
• Ability to simplify complex Agentic AI, AI/ML, and Generative AI concepts through practical examples and demonstrations.
• Experience building or demonstrating LLM-powered applications and AI agent workflows.
• Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar Agentic AI frameworks .
• Strong understanding of RAG architectures, tool calling, function calling, and LLM orchestration.
• Ability to explain AI agent architectures, planning, reasoning, memory, and multi-agent collaboration.
• Strong understanding of Artificial Intelligence, Machine Learning, Deep Learning, NLP, and Generative AI.
• Excellent communication and storytelling skills.
• Experience conducting live virtual training using Zoom, Microsoft Teams, or similar platforms.
• Strong learner engagement, facilitation, and Q&A management skills.
• Ability to conduct interactive, activity-driven learning experiences.
• Ability to connect Agentic AI concepts with real-world business use cases.

Preferred Skills

• Experience training professionals, working professionals, or adult learners in Agentic AI, AI/ML, or Generative AI.
• Experience creating Agentic AI training content, exercises, demonstrations, or case studies.
• Hands-on experience developing production-grade AI agents or agentic applications.
• Experience with multi-agent frameworks such as CrewAI, AutoGen, LangGraph, or similar technologies.
• Experience implementing RAG pipelines, vector databases, embeddings, and knowledge retrieval systems.
• Experience integrating LLMs with external APIs, databases, tools, and enterprise systems.
• Exposure to AI workflow automation and orchestration platforms.
• Experience with Python and AI development environments.
• Familiarity with emerging Agentic AI architectures, autonomous AI systems, and AI coding agents.
• Experience demonstrating AI agent use cases across different business functions.
• Strong understanding of responsible AI, AI ethics, security, bias, and governance.

Key Competencies

Student Support & Mentorship

Performance Monitoring

Collaboration & Professional Conduct

Work Schedule

• Part-Time instructors typically work 8–12 hours per week , depending on training schedules.
• Each training session is approximately 3 hours in duration.
• Sessions are delivered live in a fully online format.
• Flexibility for evening and weekend availability is preferred based on learner cohort schedules.

Compensation

• The anticipated compensation for this position is $80 per hour , depending on qualifications, experience, and alignment with programme requirements.
• Candidates with exceptional Agentic AI expertise, strong hands-on AI agent development experience, extensive industry experience, or strong instructional experience are encouraged to apply.
• This position is classified as Part-Time, Non-Exempt, and employees will be compensated for all hours worked in accordance with applicable federal, state, and local wage and hour laws.

Equal Employment Opportunity

Work Authorization