AI/ML Governance Lead, Commercial & Investment Banking Digital, Data and AI

Drive the execution of responsible AI practices across large-scale initiatives. This role places you at the center of managing risk, strengthening governance processes, and guiding teams through complex AI oversight needs. Influence outcomes by ensuring AI systems are deployed with clarity, control, and accountability.

As an AI/Machine Learning Governance Lead at JPMorganChase within the Commercial & Investment Bank’s Digital, Data and Artificial Intelligence organization, you will help set and execute the governance framework that enables responsible adoption of artificial intelligence, machine learning, and generative AI. You will partner closely with risk, legal, compliance, and technology stakeholders to translate policy into clear processes, controls, and scalable tooling. You will drive transparency through executive reporting and ensure the organization is prepared for audit, regulatory, and client requests.

Job responsibilities

• Serve as a liaison partnering with the Firmwide CAO (Chief Analytics Office) to coordinate and deliver region-specific responses to audit, regulatory, and client inquiries, ensuring all outputs are accurate, consistent, and fully evidence-supported

• Serve as the region-specific lead for promoting the CIB AI governance operating model, actively guiding and supporting teams through implementation by providing enablement, coordination across stakeholders, and ongoing oversight to drive consistent adoption

• Partner with data science, architecture, engineering, and data stakeholders to assess impacts of new policies, standards, and procedures, and translate requirements into actionable implementation plans

• Maintain and continuously improve artificial intelligence and machine learning governance documentation (procedures, charters, operating models, and job aids), including managing periodic reviews and refresh cycles

• Partner with controls management to identify, document, and monitor artificial intelligence and machine learning risks, issues, and actions through established governance forums

• Enhance and streamline governance by helping define and execute the strategic roadmap for governance tooling, including requirements definition and process standardization

• Facilitate working sessions and stakeholder forums to drive alignment, resolve blockers, and promote consistent best practices across lines of business

Required qualifications, capabilities and skills

• Formal training and/or certification in AI/ML (including GenAI) governance, and demonstrated knowledge of agentic AI concepts (e.g., orchestration, tool use, human-in-the-loop controls, and monitoring) with at least 5+ years of applied experience implementing and advising on AI/ML governance concepts

• Bachelor's degree in relevant field and relevant technical experience in AI/ML governance, model risk management, or regulatory compliance

• Experience delivering or governing artificial intelligence, machine learning, and generative AI solutions within financial services or a highly regulated environment

• Demonstrated ability to partner effectively with senior stakeholders across risk, legal, compliance, controls, business, and technology teams

• Strong written, verbal, and presentation skills, including advanced proficiency with Microsoft Excel and PowerPoint

• Strong analytical and problem-solving skills, with the ability to translate complex requirements into practical processes and controls

• Proven ability to influence across teams, build consensus, and drive adoption without direct authority

• Strong attention to detail with an ability to manage multiple initiatives, deadlines, and changes in priorities

• Strong interpersonal skills and the ability to operate effectively in a fast-moving, evolving environment

Preferred qualifications, capabilities and skills

• Familiarity with model risk management concepts and governance expectations for machine learning models

• Knowledge of banking, markets, and trading, and how analytics is applied across those domains

• Exposure to governance tooling implementation, workflow design, or controls automation initiatives