About the Role

We are looking for an experienced Agentic AI Instructor to teach a 6-week, full time immersive bootcamp focused on building production-ready agentic AI systems. The program takes learners from LLM fundamentals through RAG, single- and multi-agent systems, AgentOps, and deployment.

This role is open to in-person instructors.

For in-person delivery, instructors must be available to travel to Saudi Arabia for an initial 2-month engagement, with the possibility of extension to 9–12 months or longer.

What You Will Teach

You will guide learners through an end-to-end, capstone-driven curriculum covering:

- Python fundamentals and Generative AI basics (pre-work alignment)
- LLM fundamentals, prompting, evaluation, and safety
- AI-assisted development and “vibe coding”
- Retrieval-Augmented Generation (RAG) with vector databases
- Single-agent systems with reasoning loops and tool use
- Multi-agent systems with memory, planning, and coordination
- Agentic platforms (e.g., LangGraph, AutoGen concepts)
- Agent reliability, safety, guardrails, and AgentOps
- Observability, cost control, and performance optimization
- Deployment patterns and production-ready agentic architectures
- Capstone mentoring and technical demo preparation

Key Responsibilities

- Deliver live instruction for a full-time, 6 week bootcamp
- Lead hands-on labs, code walkthroughs, and weekly project sprints
- Mentor students through weekly mini-projects and a final capstone
- Review agentic AI codebases and provide clear, actionable feedback
- Teach students how to design, reason about, and debug agentic systems
- Guide learners in evaluating agent reliability, safety, and cost tradeoffs
- Contribute to curriculum development and continuous improvement
- Collaborate with program staff on learner progress and outcomes

Required Qualifications

- Strong hands-on experience with agentic AI systems, including:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)




- Tool-calling agents and reasoning loops
- Multi-agent architectures and memory
- Experience with Python-based AI development
- Familiarity with vector databases and embeddings
- Understanding of AgentOps / LLMOps concepts (evaluation, monitoring, cost control)
- Excellent communication skills and ability to explain complex ideas clearly
- Bootcamp teaching experience or equivalent (intensive training, workshops, mentoring)
- Proven content development experience (curriculum, labs, assignments, or technical materials)
- Ability to mentor learners through end-to-end capstone projects
- GitHub profile required (please include a link with your application)

Preferred / Nice-to-Have

- Experience teaching AI agents or autonomous systems
- Familiarity with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks
- Experience reviewing or refactoring AI-generated code
- Prior experience teaching in accelerated or immersive programs
- Experience working with enterprise, government, or international cohorts

Location & Commitment

- In-Person
- In-person role requires travel to Saudi Arabia for 2 months
- Extension possible to 9–12 months or longer based on program needs and performance
- Full-time teaching commitment during bootcamp delivery

Why Join Us

- Teach a cutting-edge, agentic AI curriculum
- Work with highly motivated learners in an immersive environment
- Be part of long-term programs with extension and growth opportunities
- Shape how the next generation of AI engineers build reliable agentic systems
- Contribute to outcome-driven, real-world AI education initiatives

How to Apply

Please submit:

- Your resume or LinkedIn profile
- A link to your GitHub profile
- A brief note describing your teaching experience and availability (remote or in-person)

Job Types: Full-time, Contract

Application question(s):

- Are you willing to travel to Saudi Arabia to teach the bootcamp?
- Do you have previous AI bootcamp teaching experience?
- Are you able to work according to the Saudi Arabia time zone?

Work Location: In person

📌 Agentic AI Bootcamp Instructor (LLMs, RAG, Agents & AgentOps) (Canada)
🏢 WeCloudData
📍 Canada