AWM Controls Strategy & Innovation (CSI) – AI Controls Enablement Lead (Vice President)

Overview

In this role you lead the AI Controls Enablement team at the intersection of business and technology, turning AI behavior into actionable risk insights and scalable automated controls. You coach and co-develop with Controls, Technology, and the business to surface the invisible and make technical solutions practical. You engage senior stakeholders to influence how AI-enabled controls are built and deployed across Asset & Wealth Management and beyond.

Responsibilities

• Develop AI tools with Citizen Developers and Technology to prototype and scale automated controls while co-signing tool submissions before deployment
• Select cost-effective AI/automation solutions (e.g., UiPath, Python, and JPMorgan-approved tools) to address business problems
• Run scenario simulations and red-team exercises; establish standards for AI tool reviews and deployment
• Lead the AI Controls Council and produce the quarterly AI Controls Intelligence Report for leadership
• Define measurable outcomes, guide solution development, and share best practices across teams

Key requirements

• Demonstrated expertise in risk or control management within financial services, focusing on compliance and operational risk mitigation
• Solid understanding of AI models, their assumptions, limitations, and failure modes
• Ability to translate technical AI behavior into documented, actionable risk findings
• Capability to implement robust controls to safeguard operations and meet regulatory requirements
• Proficiency in process and data analysis to enhance control environments and interpret business needs
• Strong leadership, judgment, and ability to influence risk culture
• Strong internal stakeholder management and collaboration with senior leaders
• Strong project management and commitment to operational excellence
• Proficiency in Microsoft Office Suite with ability to develop executive presentations

• effective communication with senior stakeholders
• collaboration across cross-functional teams
• problem solving under risk constraints
• risk management in financial services
• AI model literacy (assumptions, limitations, failure modes)
• analysis of controls in AI-enabled environments

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