Senior Technical Trainer — AI / DevOps

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Trainer — AI / DevOps based in Canada. As a Senior Technical Trainer, you will combine hands-on DevOps expertise with a passion for teaching to develop practical, engaging courses on AI-powered engineering workflows. You will help engineers understand how to apply AI agents, coding assistants, and modern AI tools to real-world infrastructure and automation challenges. Working alongside a curriculum team and experienced technical educators, you will design lessons, develop hands-on lab specifications, and record clear, compelling instructional videos. This remote freelance opportunity begins with a paid course project, typically lasting around three months, with the potential for ongoing projects or a full-time position. You will have the flexibility to work alongside existing commitments while contributing your technical knowledge to a global engineering community. The ideal candidate is a practising DevOps engineer who can simplify complex concepts, communicate confidently on camera, and create learning experiences that make advanced technologies accessible. Accountabilities - Design and develop technical courses - Collaborate with the curriculum team to define course structure, learning objectives, lesson sequences, and practical lab exercises focused on AI for DevOps. - Develop content that demonstrates how engineers use AI agents, coding assistants, and LLM-based automation in real infrastructure environments. - Ensure lessons are technically accurate, relevant, practical, and aligned with the needs of working engineers. - Create engaging instructional content - Write concise, story-driven video scripts designed to explain technical concepts clearly, with individual lessons typically lasting around six minutes. - Use AI tools where helpful during drafting while ensuring the final scripts reflect your own voice, expertise, and teaching style.

- Narrate and present lessons confidently in English, making complex technical topics approachable for learners at different experience levels. - Develop and validate hands-on labs - Write detailed specifications for practical labs that demonstrate real-world DevOps and AI workflows. - Collaborate with the dedicated labs team responsible for building the lab environments. - Test completed labs, validate technical accuracy, and ensure exercises deliver the intended learning outcomes. - Record demonstrations and walkthroughs explaining how to complete lab exercises and solve practical challenges. - Collaborate on quality and editorial development - Work closely with curriculum and production teams throughout the course development process. - Incorporate structured editorial feedback, particularly during the initial course section, to align content with established teaching standards. - Participate in regular team syncs and maintain communication through collaboration tools such as Slack. - Focus on technical expertise, teaching, scripting, and recording while the production team manages video editing, animation, lab infrastructure, and publishing. Requirements: - Hands-on DevOps and infrastructure experience - Strong practical knowledge of Linux, containers, Kubernetes, at least one major cloud platform, CI/CD, and infrastructure as code (IaC). - Experience building, operating, and maintaining infrastructure rather than relying solely on theoretical knowledge. - The ability to demonstrate real engineering workflows and translate practical experience into effective learning materials. - Current experience with AI technologies - Practical experience using AI tools in engineering work, including AI agents, coding assistants, and LLM-based automation.