AI Lead- Head of Data and AI

As the Head of Data and AI for one of the UK’s leading Utilities client of ours, you will act as the definitive 'face of IT' for all artificial intelligence and data initiatives. With the C-suite highly focused on leveraging AI to drive operational efficiency and network modernisation, this role is critical in managing executive expectations while reliably delivering high-impact solutions.

You will navigate the complex intersection of emerging technology, regulatory compliance, and business transformation to future-proof the operational capabilities.

• Executive Leadership:
  Act as the primary AI ambassador, managing C-suite expectations regarding efficiency gains and translating corporate strategy into deliverable AI roadmaps.
• Technology Delivery:
  Direct a diverse portfolio of AI initiatives spanning Traditional Machine Learning, Generative AI, and advanced Agentic AI workflows.
• Ecosystem Orchestration:
  Collaborate seamlessly with internal teams, and partners to build, scale, and deploy robust AI models.
• Stakeholder Engagement:
  Partner with senior director-level stakeholders across the business to identify process bottlenecks, design targeted AI interventions, and ensure solution alignment.
• Responsible AI (RAI):
  Design and enforce a robust RAI framework in strict coordination with Cyber Security, Risk, and Data Governance teams to ensure secure, compliant, and ethical deployments.
• Change Management:
  Lead the education of business units, demystifying AI capabilities, fostering digital literacy, and promoting secure, enterprise-wide adoption.

• Core Stack Expertise:
  Proven leadership experience directing enterprise architecture and engineering teams within modern AI/ML environments, specifically AWS Bedrock, Databricks for MLOps, and Microsoft Copilot Studio.
• Sector Knowledge:
  Deep understanding of the UK energy and utilities sector, including the unique operational, data, and security challenges inherent to the industry.
• Strategic Communication:
  Demonstrated ability to translate complex multi-agent systems and Large Language Model (LLM) capabilities into clear business value for non-technical audiences.
• Delivery Models:
  Expertise in orchestrating hybrid delivery environments, effectively blending internal engineering talent with partner-led AI Lab resources.

• Extensive background in a senior IT leadership or Enterprise Architecture capacity, successfully bridging advanced data science with enterprise strategy.
• Strong track record of delivering enterprise-grade AI/ML products that have demonstrably improved operational efficiency, automated complex workflows, and reduced costs.