Head, Governance & Architecture (Digital & AI Office)

Job Summary

We are looking for a Head of Governance & Architecture to shape how digital and AI are built, scaled, and governed across the organisation. Reporting to the Head, Digital Strategy & Transformation under the Digital & AI Office, this is a senior role for a practitioner who believes governance enables innovation, not slows it down.

You will define architecture, standards, and guardrails that enable teams to move fast while remaining secure, scalable, and aligned. Drawing on hands-on experience, you will bridge strategy and execution, ensuring technology decisions translate into real delivery and business impact.

You will also enable innovation through sandbox environments and external partnerships, bringing structure across the digital and AI ecosystem and ensuring solutions are built once and scaled effectively. This role requires a builder's mindset, architectural discipline, and the judgement to balance speed, risk, and long-term value.

Key Responsibilities

Governance Strategy & Guardrails

Define the governance approach for digital and AI, including principles, decision rights, and escalation pathways. Establish proportionate, risk-based guardrails that enable speed while ensuring appropriate oversight. Partner with IT, risk, compliance, cyber security, and data governance functions to maintain alignment.

Architecture Direction & Standards

Set reference architectures, design patterns, and platform standards for digital and AI solutions. Drive reuse, modularity, and scalability. Provide lightweight solution assurance to identify risks early. Establish fast lanes for low-risk work and structured review for complex or novel use cases.

Technology Evaluation & Integration

Evaluate and select technologies based on business needs and use cases. Assess fit within the application and data landscape. Guide integration to ensure interoperability and alignment with architecture standards.

AI Governance & Responsible Adoption

Establish AI governance guardrails to ensure solutions are safe, ethical, explainable, and compliant. Define standards for data usage, model risk, human oversight, and monitoring. Advise on high-risk or complex use cases and stay aligned with evolving regulations and industry practices.

Cyber Security & Risk Integration

Embed cyber and OT security into architecture, standards, and AI governance from the outset. Partner with cyber security teams to ensure solutions are secure by design, particularly in customer, operational, and safety-critical environments.

Templates, Playbooks & Knowledge Management

Define standards for documentation, templates, and playbooks to ensure consistency and reuse. Lead knowledge management, including AI-enabled tools, so learning is captured and scaled across the organisation.

Decision Authority & Escalation

Act as the senior escalation point for architecture and governance decisions. Provide clear direction in ambiguous situations, balancing technical, commercial, and risk considerations.

Sandbox Environment Governance & Administration

Govern enterprise digital and AI sandbox environments. Ensure secure-by-design setup, appropriate isolation, and alignment with cyber security and data protection standards. Define access controls, data policies, and monitoring to support safe experimentation and transition successful use cases into production.

External Innovation & Vendor Collaboration

Drive AI innovation through partnerships with vendors, IHLs, government agencies, and ecosystem partners. Structure AI labs and co-innovation programmes with clear governance, IP considerations, and risk controls. Ensure outputs are reusable and aligned with strategic priorities.

Team Leadership & Influence

Build and lead a team of architects and governance specialists. Influence a broader community across architecture, engineering, and data without formal authority. Foster a community of practice that drives consistency and continuous improvement.

Experience

• Minimum 10 years of experience across architecture, cloud platforms, digital and AI solutions, or transformation delivery in complex organisations
• Strong practitioner background in cloud platforms (AWS, Azure, GCP), with hands-on experience designing and scaling production-grade architectures
• Proven ability to translate architecture into delivery, including platform setup, engineering practices, and implementation guidance
• Practical experience in data and AI environments, including understanding of ML development, deployment patterns, and lifecycle management
• Experience designing governance models that enable delivery, focusing on usability, speed, and real-world outcomes
• Demonstrated experience in AI governance or responsible AI practices in enterprise settings
• Strong experience integrating enterprise systems, data platforms, and AI/ML tools into coherent architectures
• Experience embedding security-by-design principles in collaboration with cyber security teams
• Proven ability to lead teams and influence cross-functional stakeholders without formal authority

Skills & Competencies

Core

• Strong architectural thinking, with the ability to design scalable, reusable solution patterns and standards
• Hands-on understanding of modern digital, data, and AI technologies, including cloud, data platforms, AI/ML, and integration approaches
• Practical experience with cloud platforms such as AWS, Azure, or GCP
• Working knowledge of data science and machine learning concepts, including model lifecycle and deployment considerations
• Strong command of AI governance, including model risk, data ethics, explainability, and regulatory expectations
• Ability to design governance and operating models that enable delivery through proportionate, risk-based controls
• Solid understanding of cyber security and secure-by-design principles across digital and operational environments
• Strong technology evaluation and integration skills across enterprise and AI platforms
• Designs practical templates, playbooks, and review frameworks that are adopted by teams
• Strong stakeholder influence, with the ability to lead through credibility and practitioner experience
• Strong executive communication, translating technical concepts into clear business outcomes
• Comfortable operating in ambiguity and driving structured, pragmatic decisions

Preferred

• Domain experience in transport, particularly rail, bus, or large-scale operations
• Familiarity with enterprise architecture, AI governance, and cyber security frameworks
• Experience in regulated, safety-critical, or operational technology environments
• Exposure to ecosystem-driven innovation, including vendor or AI lab collaborations
• Experience across agile and traditional delivery models
• Relevant certifications in cloud, architecture, AI, cyber security, or related fields

Education & Qualifications

• Bachelor's degree in Engineering, Computer Science, Data Science, or a related field
• Master's degree or PHD in Engineering, Computer Science, Data Science, or a related field are advantageous
• Relevant certifications in enterprise architecture, AI governance, cyber security, or project management are advantageous