AI Technical Enablement Specialist

AI Technical Enablement Specialist

Commercial

About the role

Quadmark designs and delivers technical training and enablement for leading technology and AI companies. You’ll be the hands-on AI specialist our teams turn to when they need to understand a technical requirement, check that a lab works or make a complex topic clear enough to teach.

The one thing

Make sure our AI learning programmes are technically accurate, practical to run and useful to the teams and partners learning how to deploy AI.

What you’ll be responsible for

• Translate technical requirements and feedback from clients and implementation partners into clear, actionable guidance for Learner Experience, Content and Facilitation.
• Review training content, code samples, diagrams, labs and demos against current documentation and the agreed technical requirements. Run exercises from a clean setup, reproduce issues and record what passed, what needs fixing and what remains untested.
• Build or adapt small examples, labs and prototypes when they’re needed to test an approach, clarify a concept or unblock a programme.
• Help facilitators prepare for technical sessions and likely questions. Join specialist client or partner conversations when your input will help clarify a requirement or resolve an issue.

How you’ll work with the team

The Client Partnership Lead owns the client relationship and commercial commitments. The Learner Experience Lead and delivery teams own learning design and delivery. You’re responsible for the quality of your technical review and for flagging issues before release. Your hands-on work supports learning and validation. Production deployment and ongoing operation sit with the teams responsible for those systems.

What you’ll bring

• Hands-on experience building, testing and troubleshooting AI applications or API integrations. You can explain what you built, the trade-offs you made and how you checked it worked.
• Practical understanding of enterprise AI deployment, including how identity, data access, security, integration and scale affect what partners need to learn.
• Current knowledge of AI models, APIs and developer tools, with good judgement about evaluation and safe use. You can get up to speed quickly from documentation and hands-on testing.
• A clear, concise way of explaining technical ideas and giving feedback that writers, designers and facilitators can act on. Experience developing technical learning or workshops is helpful.

What success looks like

• Priority labs and demos can be run from the documented setup, with test evidence and any remaining risks recorded.
• Teams can turn partner feedback into specific content fixes and resolve technical issues before release.
• Facilitators can explain the key concepts, run the examples and handle common technical questions with confidence.