About Smart Working
At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being.
Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.
Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.
About the Role
As a Technical AI Trainer, you will design and deliver practical, hands-on AI training that enables software engineers to apply AI effectively across development, QA, and DevOps. You will own and continuously evolve the training curriculum, ensuring it remains current as AI tools, coding assistants, MCP servers, and automation capabilities rapidly evolve.
You will work alongside other trainers and curriculum contributors while independently delivering training, reviewing submitted work, and providing practical feedback. This is an internal enablement role focused on AI-assisted software delivery and is not a client delivery, presales, or client-facing consulting position. The role requires broad, hands-on software engineering knowledge across the full SDLC rather than deep expertise in a single specialism.
Responsibilities
Design and deliver hands-on AI training across Development, QA, and DevOps.
Own and continuously evolve the training curriculum to ensure it remains up to date.
Review trainees' submitted code and exercises, providing direct, practical feedback.
Stay hands-on with emerging AI tools, including coding assistants, MCP servers, and AI-driven CI/CD automation.
Deliver practical training in AI-assisted software delivery, including coding, test automation, code review, and CI/CD.
Apply broad, hands-on knowledge across the full software development lifecycle rather than a front-end or back-end specialism.
Work collaboratively with other trainers and curriculum contributors while independently designing and delivering training.
Requirements
6–9 years of hands-on software engineering experience across the full SDLC, including Development, QA, and DevOps.
2+ years of daily hands-on use of AI coding tools such as Claude Code, GitHub Copilot, or equivalent AI IDEs.
1+ year of hands-on experience with AI-assisted test automation, such as Playwright with AI test generation.
1+ year of hands-on AI-assisted code review experience.
3+ years of CI/CD pipeline configuration experience, including 6–12 months of AI/MCP-driven CI/CD automation knowledge.
2+ years of coaching, mentoring, or delivering technical training or workshops.
Strong communication skills with the ability to explain technical concepts to audiences with varying levels of experience.
A patient coaching mindset suited to supporting non-expert and mixed-skill audiences.
Curiosity and self-motivation to stay current with emerging AI tools.
Demonstrable hands-on delivery experience with AI tools rather than purely conceptual or theoretical knowledge.
Strong generalist expertise spanning Development, QA, DevOps, and the full software development lifecycle.
Nice to Have
6–12 months of hands-on experience with MCP servers (such as GitHub MCP Server) and agent-based workflow automation, or strong AI fundamentals with the ability to ramp up quickly.
1+ year of curriculum or training content development experience, or the ability to rapidly develop this capability through strong self-directed learning.
1+ year of experience reviewing or assessing code or technical exercises submitted by others.
2+ years of DevOps auto-deployment or infrastructure automation experience, or strong CI/CD fundamentals with a willingness to learn.
Experience leading projects.
A strong one-to-one mentoring track record.
