Instructor – Agentic AI
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Job Description
Part-time online Agentic AI instructor delivering hands-on training for Simplilearn bootcamp learners. Teaching AI agents, LLMs, RAG, machine learning, and automation through live classes and mentorship.
Responsibilities:
- Deliver live online instructor-led training in Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, and Large Language Models
- Explain complex AI concepts and demonstrate agentic AI architectures, workflows, frameworks, and tools
- Teach topics including AI agents, LLM applications, prompt engineering, RAG, tool/function calling, agent memory, planning, reasoning, multi-agent systems, automation, orchestration, neural networks, transformers, NLP, generative models, and responsible AI
- Prepare and continuously update presentations, learning materials, practical exercises, hands-on activities, demonstrations, use cases, case studies, templates, and reference materials
- Conduct interactive workshops, Q&A sessions, knowledge checks, guided practice, and hands-on demonstrations
- Guide learners through real-world Agentic AI scenarios and business applications
- Support learners in building LLM-powered applications and Agentic AI solutions
- Provide individualized learner support during live sessions and scheduled office hours
- Maintain communication regarding learner progress, expectations, and skill development
- Provide timely, constructive feedback on exercises, activities, and assessments
- Evaluate learner progress using participation, knowledge checks, practical exercises, and hands-on activities
- Maintain accurate learner engagement and performance records
- Identify learners needing additional support and collaborate with internal teams to improve outcomes
- Stay current with Agentic AI, Generative AI, LLM technologies, frameworks, autonomous AI systems, and industry trends
- Collaborate with curriculum and instructional teams to improve content, training quality, learner experience, and outcomes
- Foster an inclusive, collaborative, and professional learning environment
- Represent Simplilearn professionally with learners, staff, and external stakeholders
Requirements:
- 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, AI agents, LLM-powered applications, agentic workflows, automation, Large Language Models, Prompt Engineering, RAG, tool calling, function calling, AI agent memory and context management, planning, reasoning, task decomposition, multi-agent systems, LLM orchestration, Machine Learning, Deep Learning, Neural Networks, Attention Mechanisms, Transformers, NLP, text classification, BERT, GPT, GANs, VAEs, Diffusion Models, and responsible 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
- Strong instructional and learner engagement abilities
- Experience building or demonstrating LLM-powered applications and AI agent workflows
- Experience conducting live virtual training using Zoom, Microsoft Teams, or similar platforms
- Ability to conduct interactive, activity-driven learning experiences
- Ability to connect Agentic AI concepts with real-world business use cases
- Applicants must be legally authorised to work in the United States at the time of application and throughout employment
- Flexibility for evening and weekend availability is preferred based on learner cohort schedules
Benefits:
- Flexible part-time schedule of approximately 8–12 hours per week
- Compensation for all hours worked in accordance with applicable federal, state, and local wage and hour laws
- Live online work format
- Evening and weekend scheduling flexibility based on learner cohort schedules
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