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Senior Technical Trainer — AI / DevOps

jobgether

MexicoFULL_TIMEPosted 0 day(s) ago$0-$0 / yr

About jobgether

No company information provided.

About this Role.

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 Mexico.

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.

Skills Required

Benefits & Perks