Agentic AI Bootcamp Instructor in Toronto

Agentic AI Bootcamp Instructor in Toronto

Toronto Full-Time 90000 - 110000 $ / year (est.) On-site
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At a Glance

  • Tasks: Teach a 6-week immersive bootcamp on agentic AI systems and LLM fundamentals.
  • Company: WeCloudData, a leader in AI education with a focus on innovation.
  • Benefits: Competitive salary, travel opportunities, and hands-on teaching experience.
  • Other info: In-person role with potential travel to Saudi Arabia and excellent career growth.
  • Why this job: Shape the future of AI while mentoring passionate learners in an exciting environment.
  • Qualifications: Strong experience with agentic AI, LLMs, and Python; teaching experience preferred.

The predicted salary is between 90000 - 110000 $ per year.

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.

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).

Agentic AI Bootcamp Instructor in Toronto employer: Vibehackers

Life360 is an exceptional employer for Senior Backend Engineers II, offering a dynamic work culture that prioritizes innovation and collaboration. With a focus on AI-native engineering, employees have the opportunity to work with cutting-edge technologies while contributing to impactful projects that serve millions of users. The company provides comprehensive benefits, including flexible PTO, robust health insurance, and support for remote work, fostering an environment where personal and professional growth is encouraged.

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Contact Details:

Vibehackers Recruitment Team

We think you need these skills to ace Agentic AI Bootcamp Instructor in Toronto

Agentic AI Systems
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Python-based AI Development
Vector Databases
Embeddings
AgentOps / LLMOps Concepts