Agentic AI Bootcamp Instructor (LLMs, RAG, Agents & AgentOps) Explicitly references "vibe coding" and AI-assisted development as part of the curriculum.

About the Role WeCloudData seeks an experienced Agentic AI Instructor to deliver a 6-week, full-time immersive bootcamp teaching LLM fundamentals, RAG, single- and multi-agent systems, AgentOps, and production deployment. The role is in-person and requires travel to Saudi Arabia for an initial 2-month engagement with possible extension. Role WeCloudData is hiring an Agentic AI Instructor to teach a 6-week, full time immersive bootcamp focused on building production-ready agentic AI systems.

The instructor will lead an end-to-end, capstone-driven curriculum covering LLM fundamentals, prompting, RAG, single- and multi-agent systems, AgentOps, observability, cost control, and deployment patterns.

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 design, debugging, evaluation, and safety practices for agentic systems - Guide learners on agent reliability, safety, guardrails, and cost tradeoffs - Contribute to curriculum development and continuous improvement - Collaborate with program staff on learner progress and outcomes Requirements - Strong hands-on experience with agentic AI systems and Large Language Models (LLMs) - Practical knowledge of Retrieval-Augmented Generation (RAG), tool-calling agents, 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 proven ability to explain complex ideas clearly - Bootcamp teaching experience or equivalent (intensive training, workshops, mentoring) - Content development experience (curriculum, labs, assignments, or technical materials) - Ability to mentor learners through end-to-end capstone projects Preferred Qualifications - 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 with enterprise, government, or international cohorts Location & Commitment - In-person role; instructors must be available to travel to Saudi Arabia for an initial 2-month engagement - Possibility of extension to 9–12 months or longer based on program needs - Full-time teaching commitment during bootcamp delivery Job Type - Full-time, Contract How to Apply Submit your resume or LinkedIn profile, a link to your GitHub profile, and a brief note describing your teaching experience and availability (remote or in-person).

Python Large Language

Models (LLMs) Retrieval-Augmented Generation (RAG) vector databases embeddings LangGraph AutoGen LangChain CrewAI AgentOps LLMOps GitHub Skills Teaching / Instruction Mentoring Curriculum Development Communication Code Review Debugging Evaluation & Monitoring Safety & Reliability Assessment Deployment & Productionization Capstone / Project Mentoring Experience Level Senior Employment Type Full-time Contract

📌 Agentic AI Bootcamp Instructor (LLMs, RAG, Agents & AgentOps) (Toronto)
🏢 Vibehackers
📍 Toronto