Director of AI Strategy

Job Summary

The Director of AI Strategy is accountable for owning E-Bridge's AI plan and driving the AI strategy from roadmap, governance, and business alignment through to working implementation. The role leads the vibe coding programme — a staff-led innovation model where non-IT staff prototype solutions for their own workflows using approved AI tools — and governs the gated funnel that converts viable prototypes into secure, production-ready tools.

The Director works closely with business users, department heads, pedagogy and operations stakeholders, Group IT, vendors, and the implementation team to ensure AI initiatives are practical, safe, measurable, and aligned with both E-Bridge's preschool context and Group AI/IT Strategy. The mandate covers three interlocking responsibilities: owning the AI roadmap, building internal AI capability, and ensuring disciplined delivery with strong governance.

1. AI Strategy Roadmap, Governance & Delivery

• Own and maintain the E-Bridge AI plan and 3-year AI roadmap across curriculum, pedagogy, student management, operations, and management dashboards, covering the multi-project pipeline and any new additions.
• Drive execution from discovery through to production — working closely with users, staff representatives, vendors, the Data Analyst, and the implementation team to move each project through the gated funnel.
• Work with EB's and Group's AI Governance and Steering Committee (where required) to make go/no-go decisions at each phase gate and ensure alignment with data, security, and business priorities.
• Manage vendor and developer relationships for AI project delivery: scope definition, contract management, milestone tracking, quality assurance, and implementation follow-through.
• Produce and maintain the 3-year AI roadmap with annual update cycles; present quarterly steering reviews to leadership with clear progress, risks, decisions required, and business impact.

2. Vibe Coding Programme Governance

• Design and run the vibe coding cohort: intake, sprint scheduling, gate reviews, retrospectives, cycle close-outs, and practical guidance for staff-led prototyping.
• Recruit, onboard, and support department representatives during sprint cycles; ensure time protection rules are enforced in coordination with department heads.
• Provide structured hands-on guidance and asynchronous support to representatives during the prototype phase, helping users turn workflow pain points into safe AI-enabled prototypes.
• Translate staff-built prototypes into production-ready specifications for vendors and the implementation team; ensure security, data, integration, and usability standards are met.
• Manage sprint cycles to maintain quality, user relevance, and delivery timeline.

3. Group AI/IT Strategy Alignment

• Attend relevant Group-level forums and discussions, contributing to Group AI/IT strategy conversations, and representing E-Bridge's operational, pedagogical, and user requirements.
• Actively liaise with Group IT and manage enhancements of the company's Student Management System and parents and educators apps: identify optimisation opportunities for E-Bridge, raise requirements with Group IT, and track delivery against the EBMS roadmap.

4. Data & Analytics Collaboration

• Partner with the Data Analyst on dataset readiness and metric definitions that underpin AI projects.
• Co-design the data layer for flagship projects including the AI and Student Management System integrations.
• Ensure AI tools produced through the programme have measurable adoption and impact metrics; work with the Data Analyst to prepare and review adoption dashboards.

5. Stakeholder Management & Communication

• Work closely with users, department heads, and centre leaders to validate real workflow needs, secure representative nominations, protect sprint calendars, and manage escalations when department workloads create friction.
• Present AI programme updates to AI Governance and Steering Committee regularly, with clear ownership, next steps, risks, resource needs, and impact measures.

Requirements

• Relevant working experience in technology delivery, AI strategy, product management, digital transformation, education technology, or business process improvement. Formal qualifications in Computer Science, Information Technology, Engineering, Business, Education, AI, Data Science, Product Management, or related fields are advantageous but not mandatory.
• Postgraduate qualification in AI, data science, product management, or innovation management is an advantage.
• Minimum 5 years of experience in technology delivery, product management, AI strategy, or AI/digital transformation roles.
• Demonstrated track record of delivering AI or digital products end-to-end — from problem definition through to production deployment — not just advisory or strategy work.
• Experience managing external vendors, developers, and implementation teams: writing specifications, managing deliverables, and holding suppliers accountable to scope and quality.
• Experience running structured innovation programmes, agile delivery frameworks, or staff-led AI adoption programmes.
• Experience engaging with senior stakeholders and business users — ideally including group or corporate-level technology leadership — and representing a business unit's technology interests.
• Experience in an education or social services context is an advantage but not required; willingness to learn the domain quickly is essential. The candidate should be self-driven, highly motivated, and comfortable taking ownership of the AI plan with minimal supervision.

Technical Skills

• Working fluency with current AI/LLM tools and platforms (e.g. Claude, GPT-4, Gemini) — including hands-on use, prompt engineering, and practical understanding of deployment constraints.
• Practical familiarity with vibe coding / low-code / no-code tools is an advantage, as the role will guide non-technical staff in prototyping and translate useful prototypes into production-ready specifications.
• Sufficient technical depth to evaluate vendor proposals, review specifications, and identify integration or security risks without being the one writing the code.
• Understanding of data governance principles, APIs, and system integration patterns relevant to SaaS and education platforms.
• Familiarity with Microsoft 365 ecosystem (Teams, SharePoint, Power Platform) is advantageous.