Instructor - Agentic AI

Job Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Instructor - Agentic AI based in United States.

This part-time instructor role is designed for an experienced AI professional passionate about helping adult learners build practical, industry-relevant skills. You will deliver engaging, live online instruction across Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, and Large Language Models. The role combines deep technical expertise with strong facilitation, storytelling, and mentorship skills. You will demonstrate modern AI agents, RAG pipelines, multi-agent systems, orchestration frameworks, and AI-powered automation workflows. You will translate advanced concepts into practical exercises, business use cases, and hands‑on learning experiences. Working closely with curriculum and instructional teams, you will help continuously improve training quality and learner outcomes. This is an opportunity to shape the next generation of AI practitioners while staying at the forefront of rapidly evolving technologies.

Accountabilities

• Deliver live, instructor‑led online training covering Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, LLMs, and related technologies.
• Teach advanced concepts including AI agents, agentic architectures, prompt engineering, RAG, tool and function calling, agent memory, planning, reasoning, task decomposition, multi‑agent systems, and LLM orchestration.
• Demonstrate practical applications using technologies such as Lang Chain, Lang Graph, CrewAI, Auto Gen, ChatGPT, Hugging Face, AI APIs, vector databases, RAG frameworks, and workflow automation platforms.
• Prepare and continuously enhance presentations, learning materials, practical exercises, hands‑on activities, demonstrations, templates, case studies, and reference resources.
• Guide learners through real‑world scenarios involving AI agents, LLM‑powered applications, RAG solutions, intelligent automation, and multi‑step workflows.
• Facilitate interactive workshops, Q&A sessions, knowledge checks, guided practice, and hands‑on demonstrations while maintaining strong learner engagement.
• Provide individualized learner support through live sessions and scheduled office hours, offering timely feedback and practical guidance.
• Monitor learner participation, progress, exercises, and assessments, identifying learners who may require additional support.
• Collaborate with curriculum and instructional teams to improve content, training effectiveness, learner experience, and overall outcomes.
• Stay current with developments in Agentic AI, autonomous systems, Generative AI, LLMs, AI frameworks, responsible AI, and emerging industry practices.
• Foster an inclusive, professional, and collaborative learning environment while serving as an industry mentor and role model.

Requirements

• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related technical discipline.
• Experience: 10+ years of professional experience in Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, or related fields.
• Skills: Strong hands‑on experience designing, developing, implementing, or deploying AI agents, agentic systems, and LLM‑powered applications.
• Training Experience: Demonstrated experience delivering live online instructor‑led training to professionals, working professionals, or adult learners.
• Knowledge: Deep knowledge of Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, Large Language Models, and AI‑powered automation.
• Understanding: Strong understanding of agent architectures, agentic workflows, prompt engineering, RAG, tool calling, function calling, memory and contextual management, planning, reasoning, multi‑agent systems, and LLM orchestration.
• Framework Experience: Hands‑on experience with Agentic AI frameworks such as Lang Chain, Lang Graph, CrewAI, Auto Gen, or comparable technologies.
• Integration: Experience integrating LLMs and AI services through APIs and building AI‑powered automation workflows.
• Modern Techniques: Knowledge of neural networks, attention mechanisms, transformers, BERT, GPT, GANs, VAEs, diffusion models, and modern AI techniques.
• Responsible AI: Understanding of responsible AI, …