Senior Technical Trainer — AI / DevOps

Jobgether; Norway; Remote; NOK 600,000 - 900,000; Full time

Benefits offered by this job

Fixed course fee

Remote work

3‑month initial project

Potential for full-time

Global technical education team

Job summary

Jobgether represents a partner company in Norway seeking a Senior Technical Trainer — AI / DevOps. You will design practical courses on AI-powered engineering workflows, covering AI agents, coding assistants, and automation in real infrastructure environments.

This remote freelance role begins with a paid three‑month project, with potential for ongoing projects or a full‑time position. You will craft lessons, lab specs, and on‑camera explanations in English, collaborating with curriculum and

Qualifications

• Hands-on DevOps and infrastructure experience including Linux, containers, Kubernetes, CI/CD, and IaC.
• Experience with AI tools in engineering workflows and automation.
• Proven teaching or content-creation experience in technical topics.

Responsibilities

• Design and develop technical courses focused on AI for DevOps.
• Create concise video scripts and on-camera lessons in English.
• Develop hands-on labs and detailed lab specifications.
• Collaborate with curriculum and production teams and incorporate editorial feedback.

Skills

DevOps hands-on

Kubernetes

Linux

CI/CD

IaC

AI tools

Teaching

English on camera

Remote collaboration

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 Norway.

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.