Managing Director, Cybersecurity AI

Your Opportunity

Managing Director, AI Security

Schwab remains committed to providing increased visibility to career growth opportunities and job requirements. This posting announcement is part of increased transparency and while all qualified applicants will be reviewed and considered, a preferred candidate for this role has been identified.

AI is becoming increasingly embedded in client experiences, operational processes, decision support, and enterprise productivity tools across financial services. This role is critical to ensuring the firm can scale AI capabilities with strong security, governance, resilience, and regulatory discipline, protecting client and firm data while enabling responsible innovation and maintaining trust with leadership, regulators, and stakeholders.

This executive leader is responsible for setting the enterprise strategy, governance, and control environment for AI security across the firm. The role leads the development of a scalable AI security program spanning model and data protection, secure AI adoption, third-party AI risk, and regulatory readiness, while partnering closely with technology, cyber, model risk, legal, compliance, privacy, internal audit, and business leadership to enable responsible innovation in a highly regulated environment.

Key Outcomes:

• Set the enterprise vision, strategy, and multi-year roadmap for AI security, aligned with the firm’s risk appetite, business strategy, and regulatory obligations.
• Establish governance, policies, standards, and control requirements for AI use cases across development, procurement, deployment, monitoring, and retirement.
• Drive the firm’s approach to AI-specific threats and control design, including prompt injection, model manipulation, sensitive data leakage, insecure outputs, model theft, and concentration risk from external providers.
• Partner with engineering, architecture, data science, and platform leaders to embed security-by-design and risk-based approval gates across AI and machine learning lifecycles.
• Oversee AI security assessments, independent challenge, monitoring, testing, and incident response readiness for AI-enabled applications, models, and supporting infrastructure.
• Lead governance and oversight for third-party AI tools, model providers, and strategic vendors, including due diligence, contractual protections, ongoing monitoring, and exit planning.
• Translate evolving supervisory expectations, industry frameworks, and internal policy requirements into practical, auditable controls for responsible AI adoption.
• Provide clear, decision-oriented reporting to senior executives, risk committees, and other governance forums on AI security posture, material exposures, remediation priorities, and program maturity.
• Build and lead a high-performing function, influence senior stakeholders across the enterprise, and shape a culture that balances innovation, control effectiveness, and accountability.

Key Outcomes and Success Measures

• Stand up a firmwide AI security governance framework with defined ownership, approval authorities, and policy alignment across priority AI and generative AI use cases.
• Achieve materially improved inventory, classification, and risk-tiering of AI use cases, models, and external AI services across the enterprise.
• Increase the share of high-risk AI implementations subject to pre-production security review, control validation, and formal governance approval.
• Reduce the time to identify, escalate, and remediate material AI security and control issues, with transparent ownership and reporting through established governance forums.
• Improve operational resilience for AI-enabled services through defined response playbooks, scenario testing, and coordination across cyber defense, technology, legal, communications, and risk teams.
• Strengthen third-party AI oversight by implementing consistent diligence, contracting standards, monitoring, and contingency planning for critical providers and platforms.
• Deliver measurable improvement in program maturity and regulatory readiness through dashboards, control adoption metrics, independent assessments, and periodic executive review.
• Enable faster, safer adoption of AI capabilities by establishing practical guardrails that support innovation, protect client and firm data, and reinforce trust in AI-enabled decisions and operations.

Ideal Candidate

The ideal candidate is an enterprise security executive who combines deep technical and risk expertise with strong business judgment, credibility with senior leadership, and the ability to translate complex AI and cybersecurity issues into clear decisions and practical action. This leader brings a track record of building scalable control environments in regulated settings, influencing across first, second, and third lines of defense, and enabling innovation without compromising client trust, resiliency, or regulatory discipline.

• Brings executive presence, sound judgment, and the ability to influence senior business, technology, risk, and control leaders across the firm.
• Understands how to balance innovation, speed, and competitive advantage with disciplined governance, security, and regulatory expectations.
• Has operated successfully in complex, highly regulated environments where documentation, evidence, challenge, and auditability matter.
• Can connect AI security issues to enterprise risk, client impact, operational resilience, and reputation in a way that drives action.
• Builds strong teams and trusted partnerships, while leading through ambiguity, change, and rapidly evolving technology and threat landscapes.
• Pairs strategic thinking with execution discipline, ensuring the program delivers measurable outcomes rather than aspirational policy alone.

What you have

Required Qualifications

• Bachelor’s degree in cybersecurity, computer science, engineering, information systems, or a related field; advanced degree preferred.
• 15+ years of experience in cybersecurity, technology risk, security architecture, or related disciplines, including significant leadership responsibility at enterprise scale.
• Experience shaping and leading frontier AI strategy and security program at significant scale within a diversified financial services firm. 
• Demonstrated experience designing or leading security, governance, or risk programs for AI, machine learning, or advanced analytics capabilities.
• Strong knowledge of AI security risks, cybersecurity controls, data protection, cloud environments, software development practices, and third-party technology risk.
• Experience operating in a highly regulated environment with strong familiarity across governance, risk, compliance, privacy, audit, and control functions.
• Proven ability to lead cross-functional programs, influence senior executives, and drive execution across complex organizational structures.
• Exceptional written and verbal communication skills, including experience presenting to executive committees, risk forums, regulators, or boards.
• Deep expertise in AI and machine learning security, AI governance, model risk management, data protection, and control frameworks for emerging technologies.
• Strong command of cloud security, secure software development, identity and access management, resilience, and third-party risk in modern technology environments.
• Significant experience operating in highly regulated industries, with the ability to align innovation to legal, compliance, privacy, audit, and supervisory expectations.
• Executive presence and credibility to communicate complex technology, risk, and control issues to senior management, boards, regulators, and cross-functional leaders.
• Proven success building enterprise programs, leading through influence, and driving cross-functional change at scale while enabling responsible business growth.