About the role
from listingDefine the product roadmap, inspire a high-performing team, and monitor market trends to shape product innovations
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