AI Technical Content Developer at Version1

Role Purpose Own the creation and maintenance of all AI training materials, playbooks, hands-on labs, and documentation that power Version 1’s adoption programme. This role is the content engine behind the AI Champions network and broader enablement strategy, ensuring every employee has access to clear, practical, and current guidance on AI tools and ways of working. Version 1’s AI adoption targets depend on people having the right materials at the right time. The AI Champions network, training programmes, and certification pathways all require a constant flow of high-quality, up-to-date technical content. Without this, adoption stalls and best practices stay siloed. Sitting within the Enablement & Adoption function, the AI Technical Content Developer translates technical capability into practical learning. Working closely with both the Engineering and Solutions leads, this role captures new patterns, tool updates, and delivery lessons and turns them into content that Champions and practitioners can immediately use. Key Responsibilities • Create and maintain AI playbook documentation covering all phases of the software delivery lifecycle (SDLC) • Develop training materials, certification content, and practical guides for core AI tools including Cursor, GitHub Copilot, Claude, and M365 Copilot • Build hands-on lab content for the AI Champions network, with structured exercises tailored to varying technical skill levels • Design and deliver onboarding content for new AI Champions, ensuring they are productive from day one • Establish and maintain documentation standards, templates, and a centralised content library for the CoE • Collaborate with the AI Engineering lead to document new delivery patterns, automation workflows, and tooling best practices • Work with the AI Solutions & Internal Adoption lead to create user guides and adoption materials for internal AI solutions • Review and update all content regularly to reflect tool updates, new capabilities, and lessons learned from delivery • Contribute to customer-facing enablement materials where appropriate, supporting commercial consulting engagementsFY26 Objectives • Deliver complete playbook documentation covering all SDLC phases by end of Q2 • Create comprehensive training materials for 5 core AI tools (Cursor, GitHub Copilot, Claude, M365 Copilot, Copilot Studio) • Build 10 hands-on labs for Champions enablement, covering beginner to advanced use cases • Achieve less than 1 week turnaround on documentation requests from engineering and platform leads • Establish documentation standards and a templates library adopted across the CoE by end of Q1