Vice President & Head of AI Lab

Job Description

Strategy and Operating Model Execution

• Translate the bank's AI strategy into an executable portfolio of products, releases, and platform capabilities.
• Operate the AI operating model end-to-end, from intake and prioritization through delivery, deployment, and continuous improvement.
• Maintain alignment between the AI Lab roadmap, enterprise priorities, and divisional business plans.

Squad and Portfolio Leadership

• Lead two diverse squads covering customer experience AI products and internal productivity AI solutions, each with distinct missions, talent profiles, and stakeholders.
• Partner with the AI Delivery Lead to remove blockers, mitigate delivery risk, and ensure on-time release of strategic assets and committed milestones.
• Empower squad leads and product managers to operate with autonomy, clarity of priorities, and full ownership of outcomes.
• Democratization and Operationalization of AI
• Equip the organization with the right AI tools, platforms, and reusable assets to accelerate safe, productive adoption across functions.
• Build a community of practice and an enablement framework so that teams across the bank can apply AI confidently in their day-to-day work.
• Drive change management, capability uplift, and cultural reinforcement so AI becomes embedded in everyday ways of working.
• Stakeholder Management and Executive Reporting.
• Prepare and run weekly Chief Customer Officer reviews and monthly CEO updates, ensuring material is high quality, aligned with strategic priorities, and prepared well in advance.
• Build trusted relationships with department heads and squad sponsors to socialize AI opportunities and convert them into prioritized, well-scoped initiatives.
• Maintain alignment with peer leaders across Enterprise Architecture, Technology Delivery, Risk, Compliance, and other AI-related functions.

Partnerships, Ecosystem, and R&D

• Identify, evaluate, and onboard external AI providers, technology partners, and strategic investment opportunities to accelerate the bank's AI ambitions.
• Build and nurture relationships across the regional and global AI ecosystem to bring leading capabilities into the bank.
• Sustain a meaningful R&D capability within the Lab, whether through in-house experimentation, academic collaborations, or co-development with vendors and partners.
• Agile Practice and Cross-Functional Alignment.
• Operate as an active member of the Agile community, working closely with the Enterprise Project Management Office (EPMO), the Agile practice, and the relevant chapters.
• Synchronize AI Lab ceremonies, releases, and planning cycles with enterprise delivery rhythms and quarterly business reviews.

People Leadership and Development

• Build, coach, and retain a high-performing, diverse team of AI product, delivery, engineering, and science talent.
• Set clear performance expectations, invest in career development, and shape a culture of accountability, curiosity, and disciplined execution.
• Financial Accountability.
• Own the AI Lab's CapEx and OpEx envelope in collaboration with the AI Delivery Lead and Finance partners.
• Ensure the program is delivered within budget and that investment decisions are tied to measurable business outcomes.

Decision-Making Authority

• Prioritization and sequencing of the AI Lab portfolio within the agreed strategic envelope.
• Selection of AI tooling, platforms, and architectural patterns within enterprise governance.
• Selection and onboarding of AI vendors, partners, and research collaborators.
• Resourcing decisions across the squads, including hiring, talent allocation, and role design.
• Release and go-live decisions for AI products, in coordination with Risk, Compliance, and Technology partners.

What We Are Looking For

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative or technology discipline. A Master's or post-graduate qualification in AI, Data Science, or a related field is a plus but not required.
• 10 to 12 years of progressive experience across AI, data science, advanced analytics, or technology product delivery, with at least 3 to 4 years leading teams of engineers, data scientists, or AI product talent.
• Hands-on experience delivering AI or analytics products end-to-end, from concept through production and adoption. Direct experience with Generative AI is preferred.
• Experience working in banking, financial services, or another regulated industry is preferred. Exceptional candidates from technology, consulting, or product backgrounds with strong domain partners will also be considered.
• Demonstrated ability to manage a portfolio of initiatives, executive-level stakeholders, and a meaningful budget.
• Comfortable operating inside an agile delivery environment and partnering with product, engineering, and control functions.

Required Competencies

• AI and Machine Learning Strategy: Expert
• Generative AI, Large Language Models, and Agentic Systems: Expert
• AI Product Delivery and MLOps: Expert
• Cloud and Data Platforms: Advanced
• AI Governance, Responsible AI, and Model Risk: Advanced
• Solution Architecture for AI: Advanced
• Cybersecurity and Data Privacy Awareness: Advanced