CIB AI Governance Lead – Vice President

As an AI/Machine Learning Governance Lead at JPMorgan Chase 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: - Support the definition and adoption of the in-business analytics ownership operating model, including clear roles, responsibilities, and decision rights across stakeholders - Act as the primary point of contact for the business, guiding their use cases through the AI/ML Lifecycle and providing clear, customer-service-style support across multiple communication channels. - Develop deep expertise and in-depth knowledge across a select portfolio of AI/ML initiatives and projects within the CIB, partnering with business stakeholders at all levels to identify common patterns, themes and streamline solutions. - Maintain, continuously improve, and remain proficient in AI/ML governance documentation (procedures, charters, operating models, and job aids), and effectively apply it to day-to-day responsibilities; manage periodic reviews and refresh cycles to keep materials current. Partner with risk, legal, compliance, data and technology stakeholders to assess impacts of new policies, standards, and procedures, and translate requirements into actionable implementation plans - Coordinate and drive end-to-end execution of Commercial & Investment Bank-wide rollout plans, including communications, milestones, dependencies, and adoption tracking - Partner with controls management to identify, document, and monitor artificial intelligence and machine learning risks, issues, and actions through established governance forums - Serve as a liaison and quality control point for audit, regulatory, and client inquiries, ensuring responses are accurate, consistent, and supported by evidence - 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: - 5+ years of applied experience in one or more of the following areas: Audit, Controls, Compliance, Risk or Technical Product Management. - Experience delivering or governing artificial intelligence, machine learning, and generative AI solutions within financial services or other highly regulated environment - Strong analytical and interpersonal skills with the ability to translate complex requirements into practical processes and controls, while operating effectively and collaborating across a fast-moving, evolving environment. - Analytical and problem-solving skills with the ability to assess novel use cases against evolving policy and regulatory expectations - Experience partnering with technology, legal, compliance, and business stakeholders to operationalize governance requirements - Proven ability to influence across teams, build consensus, and drive adoption without direct authority - Strong project management and attention to detail with the ability to manage multiple concurrent initiatives and deadlines, adapt to shifting priorities, and clearly communicate status. Preferred qualifications, capabilities and skills: - Formal training or certification in AI/ML governance concepts - Strong understanding of machine learning lifecycle, model validation concepts, and emerging generative AI/LLM risk considerations - Familiarity with data governance, third-party/vendor risk management, and technology audit practices - Working knowledge of AI/ML tools, platforms, and techniques (e.g., LLMs, agentic AI) sufficient to engage credibly with technical teams