International Consumer Banking AI/ML Governance Control Manager - Vice President

About the job

Responsibilities

• Own and maintain the AI/ML governance risk and control view for ICB CDAO, supporting oversight and data privacy, governance, permitted use, quality, protection, retention, storage, and analytics.
• Lead the end-to-end lifecycle of AI/ML governance control issues, including intake, classification, root cause analysis, action planning, milestone management, validation, closure, and sustainability checks.
• Run AI/ML governance control routines and reporting, including governance forums, management information, and executive-level updates on control performance, issues, trends, and emerging risks.
• Define and maintain control expectations, inventory, testing approach, evidence standards, and performance monitoring; challenge design adequacy and drive measurable uplift where controls are weak or inconsistent.
• Partner across lines of defense to deliver consistent risk practices, including control design reviews, risk mitigation plans, issue management, and governance effectiveness assessments.
• Ensure alignment with applicable policies, standards, and regulations; manage exceptions and strengthen adherence through monitoring, guidance, and escalation.
• Lead control environment enhancements in response to firmwide initiatives, regulatory expectations, and industry developments; drive implementation to completion across geographies.
• Lead and coordinate end-to-end audit and regulatory exams and responses for ICB CDAO, including interactions with global regulators; own tracking and closure of resulting actions with clear accountability and evidence.

Requirements

• Demonstrated subject-matter capability in AI/ML use case and model governance and oversight, with experience across the full model lifecycle, including GenAI/LLM patterns and third-party/open-source/hosted model components.
• Advanced proficiency in model risk management, utilising techniques to identify, assess, mitigate risks and apply controls throughout the AI model lifecycle.
• Apply skills in bias detection and mitigation, ensuring AI/ML models produce fair and ethical outcomes.
• Ensure AI regulatory compliance by applying in-depth knowledge of relevant regulations and internal standards and policies to AI/ML systems.
• Significant relevant experience in operational risk, internal controls, audit, and/or control management within complex regulated environments.
• Strong expertise in operational risk and internal control frameworks, including assessment, testing/validation, issue remediation, and governance reporting within retail banking.
• Hands-on experience with Risk Control Self-Assessment (RCSA) / CORE-type processes, operational risk issue management, and control deficiency remediation.
• Experience leading cross-functional initiatives with measurable outcomes; ability to diagnose problems, define root cause, and drive execution to closure.
• Strong judgment under pressure; ability to manage competing priorities and non-negotiable deadlines.
• Clear, concise communication skills (written, verbal, and presentation), with the ability to influence senior stakeholders and escalate effectively when needed.
• Ability to challenge constructively, resolve conflicts, and enforce accountability across stakeholders.
• Familiarity with AI/ML control frameworks and translating policy/standard requirements into testable controls, measurable KPIs/KRIs, and evidence standards.
• Experience in technology, data, or analytics control environments (e.g., technology risk and controls, IT audit, data/analytics governance, SDLC/ML lifecycle controls).
• Comfortable operating in agile/digital-first delivery models and using delivery tools (e.g., Jira, Confluence).
• Management-level experience at a large financial institution, regulator, or consulting firm; experience supporting the build-out of a new retail/digital bank is a plus.