Senior Technical Trainer — AI / DevOps

Job description

**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 United States.** 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. - Genuine curiosity about emerging AI capabilities and a commitment to staying current with new tools and techniques. - The ability to explain how AI can support infrastructure engineering and DevOps workflows; deep specialization in AI research is not required. - **Teaching and communication skills** - A demonstrated passion for teaching, supported by experience creating courses, publishing tutorials, delivering talks or workshops, mentoring colleagues, or sharing technical knowledge with a community. - Excellent written and spoken English, with the ability to communicate clearly, naturally, and confidently on camera. - Strong storytelling skills and the ability to break down complex technical concepts into simple, structured explanations. - Empathy for learners, particularly beginners, and an understanding of how to make technical material engaging and accessible. - **Collaboration and adaptability** - Willingness to follow an established teaching methodology and incorporate constructive editorial feedback. - Ability to work independently, organize deliverables, and meet an agreed project schedule. - Comfort working remotely with a distributed team, including participation in weekly syncs and some time-zone overlap with colleagues based in Europe and Asia. - **Additional qualifications considered an advantage** - Previously published online courses on platforms such as Udemy or Pluralsight, or experience authoring a technical book. - Experience speaking at conferences or meetups, maintaining a technical YouTube channel or blog, or contributing to technical communities. - Community credentials or roles such as CNCF Ambassador, AWS Community Builder, or Microsoft MVP. - Relevant Kubernetes certifications, including CKA, CKAD, or CKS, or recognition such as Kubestronaut. - Cloud certifications from providers such as AWS or Microsoft Azure. ## Benefits: - **Competitive fixed fee per course**, agreed upfront based on course length and topic complexity, with higher compensation for advanced topics and exceptional instructors. - Paid freelance project that can be completed alongside an existing job, with no fixed weekly-hour requirement. - A typical initial project duration of approximately three months, with a mutually agreed delivery plan. - Potential to progress to a full-time role or take on additional course projects based on mutual fit. - Fully remote working arrangements with flexible hours. - Opportunity to collaborate with a global technical education team and reach a community of more than one million engineers. - Dedicated production support for video editing, animation, lab infrastructure, and course publishing, allowing you to focus on teaching and technical content. - Opportunity to share your expertise in AI, DevOps, cloud, and Kubernetes through practical, hands-on education.