Senior Technical Trainer — AI / DevOps Remote, worldwide

Job description

### Senior Technical Trainer — *AI* / DevOps **Remote, worldwide · Freelance course project with a path to full-time** We’re hiring on behalf of a global hands-on tech-education platform used by over a million engineers to learn DevOps, *cloud*, Kubernetes and *AI*. Its courses are built around real labs, not slides, and taught by practising engineers who are great on camera. We’re looking for a DevOps engineer who loves teaching to create and present a course on *AI* for DevOps: how engineers use *AI* agents and modern *AI* tooling in real infrastructure work. This role suits you if you already teach as part of what you do: you’ve published courses on Udemy, Pluralsight or YouTube, written a book, worked in DevRel, run workshops, or regularly speak at meetups and conferences. **How it works** - **It starts with one paid course project.** You can do it alongside your current job. There’s no fixed weekly-hour requirement, just a delivery plan you agree on together. A typical project takes around 3 months. - **The goal is long-term.** The team is growing its internal trainer pool, and the first project is how both sides find out if it’s a fit. After that, it can lead to a full-time role or more course projects. - **A fixed fee per course is agreed upfront,** based on course length and topic complexity. Fees are competitive, and advanced topics and exceptional instructors are paid accordingly. Payment is made on delivery of the completed course. - **Fully remote with flexible hours.** Expect a weekly sync, Slack communication, and some time-zone overlap with a Europe/Asia-based team. **What you’ll do** - Shape the course with the curriculum team: sections, lessons, and hands-on labs. - Write lab specs that a dedicated labs team builds, then test them. - Write and narrate short, story-driven video lessons (about 6 minutes each). You’re welcome to use *AI* to draft, but the final script should sound like you. - Record demo and lab-solution walkthroughs. - Work through structured editorial feedback, especially on your first section. Video editing, animation, lab infrastructure and publishing are all handled by the production team. You focus on the teaching. **What we’re looking for** - **Hands-on DevOps foundations:** Linux, containers, Kubernetes, a major *cloud*, CI/CD, IaC. You build and run infrastructure yourself. - **Real, current use of** ***AI*** **in your engineering work:** *AI* agents, coding assistants, LLM-based automation. Deep *AI* specialisation isn’t required, but curiosity and staying current are. - **Excellent spoken and written English.** All courses are scripted, narrated and delivered in English, so you need clear, natural, easily understood English and confidence on camera. - **A genuine passion for teaching,** shown through courses, tutorials, talks, workshops or mentoring you’ve done because you enjoy it. - **The ability to explain complex topics simply,** with empathy for beginners. - **Clear, engaging spoken English and confidence on camera.** - **Openness to an established teaching methodology** and to editorial feedback. **Nice to have** - Published online courses or a book. - Conference talks, a growing YouTube channel or blog, or community roles (CNCF Ambassador, AWS Community Builder, Microsoft MVP, etc.). - Kubernetes (CKA/CKAD/CKS, Kubestronaut) or AWS/Azure certifications. **How to apply** Send your CV or LinkedIn profile, plus a link that shows how you teach: a course, a talk, a tutorial or a short video.