Your opportunity

Director, Head of AI Risk Governance

At Schwab, you’re empowered to make an impact. Here, innovative thinking and creative problem solving help us challenge the status quo and transform the finance industry together.

The Artificial Intelligence (AI) Risk Oversight team, part of Model Risk Oversight within Corporate Risk Management, leads Schwab’s enterprise AI risk governance program. The team provides the governance framework, oversight practices, and independent challenge needed to support responsible adoption of generative and agentic AI across the Company, while aligning use cases with internal policy requirements, regulatory expectations, and industry practices.

This role combines technical fluency in the AI lifecycle with enterprise leadership to advance Schwab’s AI risk governance operating model, including policies, standards and procedures, inventory strategy, risk assessment, executive reporting, stakeholder engagement, and effective challenge across key business and control functions.

We are looking for a senior leader who can set direction, develop talent, and translate AI risks, regulatory expectations, and business priorities into a practical, scalable oversight program. This role will serve as Director, Head of AI Risk Governance, and will be responsible for:

• Set the strategic direction and roadmap for the Company’s AI risk governance program and lead the AI Risk Oversight team.
• Serve as the enterprise coordinator and convener for AI risk governance activities, bringing together stakeholders across technology, cyber, risk, compliance, legal and business functions to drive consistent oversight and governance outcomes.
• Lead interdisciplinary reviews of the Company’s generative and agentic AI use cases, in alignment with the established policies and procedures.
• Apply deep technical expertise across the entire AI lifecycle, including initial intake and assessment, testing, effective challenge, use, control framework and monitoring.
• Develop executive-ready materials and report on the AI risk governance framework, aggregate and individual AI risks, key metrics, issues and remediation activity, and emerging risk trends.
• Design and maintain AI risk policies, standards, procedures, program documentation, training, communications, change management routines, and adherence monitoring.
• Perform any other responsibilities related to model risk governance as needed.

What you have

Required Qualifications

• Master’s degree in a relevant field.
• Experience in financial services, banking, brokerage, or other highly regulated industry.
• Extensive experience risk management functions in a complex organization, including building or maturing enterprise governance programs.
• Experience managing, developing, and prioritizing teams, including setting goals, providing feedback, coaching team members, and managing performance.
• Strong knowledge of AI techniques, implementation patterns, lifecycle risks, guardrails, governance practices for generative and agentic AI.
• Demonstrated ability to influence senior leaders and drive outcomes across large, matrixed organizations without direct authority.
• Exceptional executive communication and stakeholder influence skills, with the ability to translate complex AI risk matters into clear, defensible materials.
• Recognized for building trusted relationships and collaborating effectively across diverse stakeholder groups.
• High attention to detail, strong ownership, sound judgment, and commitment to producing accurate, well-supported, and thoughtfully reviewed work products.

Preferred Qualifications

• Knowledge with AI risk management guidance and frameworks such as FSB’s Sound Practices for Responsible Adoption of AI: Consultation report, NIST AI RMF, SR 26-2, FHFA Advisory Bulletin 2022-02, EU AI Act concepts, and other relevant regulatory and industry practices.
• Experience preparing materials for regulators, internal audit, external audit, risk committees, governance forums, executive leadership, or board-level stakeholders.
• Experience building governance routines for AI inventories, risk assessments, monitoring plans, control testing, adherence monitoring, reporting, exception management, and issue remediation.