Senior Executive Director of Data & AI

Join JPMorganChase as a senior leader shaping the future of responsible data and AI governance at enterprise scale — where your expertise directly influences how one of the world's largest financial institutions innovates with integrity. In this high-visibility role, you will have the opportunity to build and lead a function that sits at the intersection of technology, risk, and regulatory strategy, with direct access to executive leadership and firm-wide impact. As a Senior Executive Director of Data & AI at JPMorganChase within Employee Platforms, you will be responsible for establishing and overseeing the enterprise framework governing data, artificial intelligence, machine learning, analytics, and emerging AI technologies. You will lead the design, implementation, and continuous enhancement of governance, risk management, compliance, and control practices that ensure responsible, secure, transparent, and regulatory-compliant use of data and AI across the organization. This role serves as the senior liaison between Technology, Data Management, Cybersecurity, Risk, Compliance, Legal, Audit, and business stakeholders — enabling innovation while maintaining a robust risk and control environment. Job responsibilities Define and execute the firm's Data and AI Governance strategy and operating model, establishing policies, standards, procedures, and controls across data, analytics, AI, generative AI, machine learning, and agentic solutions Lead governance for AI and generative AI initiatives throughout their full lifecycle, ensuring alignment with internal policies, model risk requirements, regulatory expectations, and responsible AI principles Design and maintain an effective control environment across data and AI platforms, identifying, assessing, and mitigating operational, regulatory, privacy, cyber, model, and technology risks Partner with technology teams to embed controls into data pipelines, AI platforms, and development lifecycles, and drive remediation of audit findings, regulatory observations, and control weaknesses Monitor evolving global regulatory requirements impacting data and AI, coordinating regulatory examinations and internal audit reviews while serving as the senior escalation point for governance and compliance matters Establish enterprise standards for data quality, lineage, metadata, classification, and access management, overseeing data quality monitoring, issue management, and exception reporting Define governance practices for data access, entitlement management, and least-privilege principles, partnering with cybersecurity and platform teams to establish secure, scalable, and auditable access models Chair or participate in governance forums responsible for AI and data oversight, presenting risk, control, and compliance metrics to executive committees Lead and develop a high-performing team of governance, risk, controls, data management, and AI policy professionals, fostering a culture of accountability, innovation, and responsible AI adoption Required qualifications, capabilities, and skills Formal training or certification on technology risk and controls concepts and 10+ years applied experience 5+ years of senior leadership experience managing large-scale enterprise programs and cross-functional teams Demonstrated expertise in data governance, AI and machine learning risk management, technology risk, operational risk, and internal controls Proven experience designing and implementing governance frameworks for enterprise-scale data and AI ecosystems Deep knowledge of data privacy, regulatory compliance, and audit and examination management within complex technology environments Experience developing controls supporting AI explainability, transparency, fairness, bias monitoring, human oversight, and model performance management Strong executive communication and stakeholder management skills, with the ability to influence senior leaders across technology, risk, compliance, and business functions Preferred qualifications, capabilities, and skills Advanced degree in Technology, Data Science, Business, Law, or Risk Management Industry certifications such as Certified Data Management Professional (CDMP), Certified in Risk and Information Systems Control (CRISC), Certified Information Security Manager (CISM), or Certified Information Systems Security Professional (CISSP) Experience with cloud and AI platforms such as AWS, Azure, or Databricks, including associated governance and compliance tooling Prior experience in a highly regulated financial services organization with direct exposure to regulatory examinations and supervisory engagements Familiarity with enterprise AI governance frameworks, responsible AI principles, and emerging global AI regulatory standards