International Consumer Banking AI/ML Governance Control Manager

Are you ready to make a meaningful impact in the world of AI/ML governance? Join our International Consumer Banking Chief Data & Analytics Office, where you will help shape the future of responsible AI adoption. You will collaborate with diverse teams, drive firmwide programs, and grow your career in a dynamic, innovative environment. At JPMorganChase, you will find opportunities for mobility, skill development, and the chance to contribute to industry-leading initiatives.

As an AI/ML Governance Control Manager within the International Consumer Banking team, you will own oversight and continuous improvement of the AI/ML governance control environment. You will partner with Technology, Compliance, Legal, Audit, and Operational Risk stakeholders to assess control health, drive remediation, and implement global programs. You will be accountable for control management across four pillars: Risk Identification & Assessment, Control Design & Evaluation, Issues & Control Deficiencies, and Control Governance & Reporting. You will help foster a culture of safety, compliance, and innovation, ensuring our AI/ML adoption is sustainable and impactful.

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.

Required qualifications, capabilities, and skills

• 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.

Preferred qualifications, capabilities, and skills

• 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

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