About this role
Job Description: AI & Governance – Technical Manager
We are seeking an experienced AI Transformation Project Manager to lead and accelerate AI adoption across the ORG wide Security. Operating in a highly regulated environment governed by PCI DSS and GDPR, this role drives AI-led productivity, use-case adoption, and end-to-end process transformation in close alignment with our North Star strategy and Security Roadmap. The ideal candidate combines strong programme and project management discipline with a passion for AI deployment, change management, and delivering measurable business value, all while upholding the highest standards of information security and data protection.
Required Skills & Experience:
• 12 – 15 years of overall professional experience, with a strong track record in project / programme management of technology or transformation initiatives. • Demonstrated experience driving AI, digital, or productivity-led adoption and transformation programmes at scale. • Practical understanding of enterprise AI / GenAI tools and how to embed them effectively into business workflows. • Experience operating within the payment’s technology and / or information security domain. • Working knowledge of PCI DSS, GDPR, and core information security and data protection principles. • Excellent stakeholder management, change management, communication, and influencing skills. • Strong analytical mindset, with experience defining KPIs / OKRs and tracking adoption and benefits realisation. • Ability to operate in a regulated, security-sensitive environment with strong governance discipline. • Ability to work remotely with minimal supervision, adapt to changing priorities, and interact effectively with diverse teams. • Portfolio or program management experience across cross-border teams and business units.
Key Responsibilities:
• AI Penetration & Adoption: Drive the adoption and depth of AI across Security, expanding reach and usage across teams. • AI Transformation Portfolio: Manage and maintain the AI transformation portfolio; monitor progress and unblock technical and organizational barriers with strong leadership. • Agentic AI & Autonomous Tasks: Define and oversee agentic AI initiatives, including autonomous task execution and decision-support automation; establish ethical guardrails, monitoring, containment measures, and human-in-the-loop requirements; validate outcomes and ensure safe production deployment. • Awareness & Engagement: Increase AI awareness in Security through inspiration sessions, webinars, and tech talks to sustain momentum. • North Star Alignment: Ensure all AI initiatives are designed and prioritized in alignment with the Group Security North Star strategy and security objectives. • Use Case Identification & Adoption: Identify, prioritize, and scale high-value AI use cases; build and manage a use-case pipeline and adoption roadmap with clear ownership. • Process Transformation: Lead AI-enabled process transformation to improve efficiency, quality, turnaround time, and operational excellence. • Programme & Project Delivery: Plan, govern, and deliver AI adoption projects end-to-end (scope, timelines, budget, dependencies, risks, benefits realization). • Change Management & Community Building: Drive change management, training, communications, and AI communities of practice to sustain adoption and cultivate adoption champions. • KPI & Benefits Realisation: Define and track KPIs and OKRs to measure AI adoption, productivity gains, and value delivered; report progress to leadership. • Stakeholder Management: Partner with security leaders, CISO office, product, engineering, and business teams to align priorities and remove blockers. • Governance, Risk & Reporting: Maintain robust governance over AI adoption, manage risks, and provide transparent reporting on adoption, value, and compliance.
Security & Compliance Focus:
• Ensure all AI adoption initiatives comply with PCI DSS, GDPR, and internal information security and data security policies. • Partner with the CISO office, Information Security, and Data Privacy teams to enable responsible, compliant, and secure AI usage. • Safeguard sensitive cardholder and personal data; enforce data classification, handling, and protection standards across AI use cases. • Embed security-by-design and privacy-by-design principles into AI-enabled processes, tools, and ways of working.
Preferred – Good to Have:
• Exposure to AI governance, responsible AI, or AI risk management frameworks. • Familiarity with North Star and OKR-based strategic execution. • Experience establishing AI champion networks and communities of practice within a large organisation.