Product Director - AI Governance Transformation

Ignite your passion for product innovation by leading customer-centric development, inspiring solutions, and shaping the future with your strategic vision and influence.

As a Product Director at JPMorganChase within Corporate Technology, you will set product strategy and drive the transformation of how the firm governs AI and machine learning across its lifecycle — from intake and risk review to deployment, monitoring, and decommissioning. You will lead the strategy and execution of a portfolio of AI governance capabilities that operationalize the firm’s internal AI policies, standards, and control frameworks, enabling teams to build and scale AI responsibly. You will partner across AI/ML business and engineering teams, Model Risk, Legal, Compliance, Privacy, Cybersecurity and Technology Controls, and Data Governance teams and to translate firm policy and control requirements into scalable, embedded product experiences — accelerating time-to-value for AI while strengthening trust, transparency, and resiliency.

Job responsibilities

• Leads the transformation of legacy governance processes into modern, self-service, controls-by-design product experiences that reduce cycle time and audit burden without weakening oversight
• Defines and owns the product strategy and delivery of measurable outcomes for AI governance products and platform capabilities spanning the AI/ML lifecycle.
• Drives end-to-end product delivery from discovery through launch, adoption, and continuous improvement, with clear success metrics for customer satisfaction, cycle time, and governance effectiveness
• Partners with engineering and design to deliver intuitive workflows for AI asset registration, governance evidence capture, and ongoing change management.
• Enables product operating rhythms, including quarterly planning, dependency management, and transparent executive-level reporting
• Leads cross-functional decision-making across Model Risk Management, Legal, Compliance, Privacy, Cybersecurity and Technology Controls, Data Governance, and AI/ML business and engineering teams to ensure integrated delivery
• Builds and maintains a strong feedback loop with business users, CDAO leads, and control partners, leveraging data, research, and service insights to guide iteration
• Manages product lifecycle governance, including documentation, deprecation planning, and change management to minimize disruption during the transformation
• Influences stakeholders through clear narratives, business cases, and trade-off frameworks that align product, risk, and technology leaders to a shared direction on responsible AI at scale

Required qualifications, capabilities, and skills

• 10+ years applied product management experience including delivery of governance platforms or transformation initiatives at enterprise scale
• Demonstrated experience owning strategy, roadmaps, and delivery for large-scale platform or governance products used by multiple teams across an enterprise
• Proven ability to lead cross-functional transformation initiatives across product, engineering, risk, compliance, legal, and operations, including sunsetting legacy processes and driving enterprise adoption of new tooling
• Working knowledge of AI/ML concepts and the AI/ML lifecycle how governance and controls attach to each stage
• Experience translating internal policies, standards, and control frameworks into product requirements and self-service tooling
• Ability to define clear success measures (customer satisfaction, review cycle time, control effectiveness, adoption) and drive continuous improvement against them
• Strong communication and influence skills, including executive-ready storytelling and stakeholder alignment in complex, control-sensitive environments
• Demonstrated ability to manage ambiguity, simplify complex policy and technical problems, and make sound trade-offs under constraints

Preferred qualifications, capabilities, and skills

• Prior experience in AI Governance, AI/ML platforms, or Data Governance product management and transformation initiatives within a large enterprise
• Awareness of the external AI governance landscape (e.g., emerging industry standards and regulatory expectations) and ability to translate that awareness into internal policy and product implications
• Familiarity with GenAI-specific governance considerations, including evaluations, use of third-party and open-source models, and human-in-the-loop controls.
• History of strong partnership with enterprise technology and risk teams to standardize platforms, reduce duplication, while improving customer outcomes and user experience
• Experience managing product managers and establishing product standards, playbooks, and operating routines across a portfolio
• Experience with adjacent control frameworks — data lineage, access controls, privacy, cybersecurity — and how they integrate with AI governance