AI Risk Oversight, Director

About this role

BlackRock is one of the world’s leading asset management firms, committed to helping investors build better financial futures. We bring together the best of technology and investment expertise to deliver innovative solutions across markets and geographies. Risk management is central to our mission, and data and technology are among our most important assets, serving as key differentiators for both the firm and our Aladdin business.

Business Overview

Our Risk & Quantitative Analysis (RQA) group provides independent oversight of BlackRock’s fiduciary and enterprise risks. The Enterprise Risk Management (ERM) function within RQA oversees risks that directly impact the corporate entity, including operational, technology, third party, model, and data risk, rather than the fiduciary risks assumed by funds and clients.

As a second line of defense function, our mission is to ensure senior management has defined and implemented effective risk management controls that protect our clients and our firm, while supporting the achievement of firm-wide business goals within our risk tolerance. RQA is committed to investing in our people to build both individual capability and a strong, collaborative team, within a culture of inclusion that encourages teamwork, innovation, and the development of future leaders.

The Opportunity

Artificial intelligence is rapidly becoming embedded across BlackRock’s technology, investment, operating and client-facing platforms. As AI capabilities move from experimentation into production, the firm must manage not only the risks inherent in models, but also the broader ecosystem through which AI is built, accessed, deployed and operated.

We are seeking a Director to lead AI Risk Oversight within Enterprise Risk Management . This role will provide independent oversight and challenge across the end-to-end AI lifecycle, focusing on how AI systems are built and governed, where models and AI services operate, how they access firm data and systems, and how they are safely deployed into production.

The successful candidate will bring together risk considerations that span traditional organizational boundaries. This includes AI model (including agentic AI) and deployment risks, AI infrastructure and architecture, access management, third-party party enablement and native AI usage, cybersecurity dependencies, production monitoring, and AI compute and inference risk .

This individual will partner closely with Model Risk Management, Technology and Cyber Risk, Third Party Risk, Information Security, Engineering and first line AI owners to establish a holistic view of AI risk across the firm. The role requires someone who understands both the technical architecture supporting modern AI systems and the risk and governance frameworks required to deploy them safely at enterprise scale.

Key Responsibilities

AI Risk Oversight

Provide independent oversight, review, and challenge of AI risk across the firm, assessing how AI capabilities are designed, governed, implemented, deployed and monitored, and holding first line owners accountable for managing risks within the firm’s risk tolerance.

AI Architecture, Infrastructure and Deployment Risk

Assess the technology architecture and operating environment supporting AI, including model and data pipelines, access and entitlements, production deployment, cloud and compute infrastructure, GPU utilization and cybersecurity dependencies, ensuring appropriate controls exist as AI moves from development into production.

Model Behavior and Production Risk

Oversee risks arising from AI models operating in production, including human oversight and controls around generative and agentic AI, partnering closely with Model Risk Management to provide complementary oversight beyond traditional model risk.

Third-Party Enablement and AI Risks

Partner with Third Party Risk to assess end-to-end risks associated with external AI models, platforms and infrastructure, including vendor dependencies, data and system access, model changes, cloud and compute concentration, and the controls governing third-party AI from selection through production deployment.

AI Incidents and Operating Events

Provide independent oversight of AI-related incidents and control issues, challenging root cause analysis and remediation, identifying systemic or emerging themes, and ensuring material risks and unresolved issues are appropriately escalated.

Metrics, Risk Indicators and Reporting

Develop an enterprise view of AI risk through meaningful metrics, risk indicators and senior-level reporting, translating technical risks across models, deployments, infrastructure, third parties and controls into clear assessments of residual risk for senior management, committees and boards.

Governance and Stakeholder Engagement

Serve as a senior RQA leader connecting AI risk across Model Risk Management, Technology and Cyber Risk, Third Party Risk, Data Risk, Legal & Compliance, Privacy and business technology teams, ensuring clear accountability and an integrated approach to managing AI risk across the firm.

Leadership Expectations

Build and lead a credible AI risk capability within RQA, combining technical understanding with independent risk judgment to challenge senior AI, engineering and business leaders and communicate complex AI risks clearly to executive and board-level audiences.

What We Look For

• •Enterprise experience across model risk, AI/ML governance, technology risk, enterprise risk, engineering risk, model implementation or a closely related control discipline , ideally within financial services or another highly regulated environment.
• •Strong understanding of the AI/ML lifecycle , including model development, validation, integration, deployment, inference, monitoring and production operations.
• •Experience with model governance and model implementation , with an ability to distinguish traditional model validation from the broader technology and operational risks associated with deploying AI at enterprise scale.
• •Strong understanding of modern AI architecture and infrastructure, including model APIs, data and inference pipelines, cloud environments, compute/GPU infrastructure, access management and production deployment patterns .
• •Understanding of risks associated with generative and agentic AI , including hallucination, reliability, data access, third-party models and the use of AI within automated or agentic workflows.
• •Experience assessing third-party technology or AI risk , including dependencies created through external models, platforms, cloud infrastructure and AI service providers.
• •Ability to assess the effectiveness of technical and operational controls and provide credible independent challenge to senior engineers, AI practitioners and business leaders.
• •Demonstrated experience developing risk metrics, indicators and senior management reporting that translate complex technical issues into clear assessments of risk.
• •Excellent judgment and critical reasoning, with the ability to differentiate between theoretical AI risks and risks that are material in real-world enterprise production environments.
• •Strong communication and influencing skills, with the ability to operate credibly with senior technology, risk and business executives.
• •Familiarity with established and emerging AI and technology risk frameworks, such as the NIST AI Risk Management Framework, NIST Cybersecurity Framework and model risk management principles , is preferred.
• •A bachelor's degree in computer science, engineering, mathematics, statistics, finance, risk management or a related discipline is required; an advanced degree or relevant professional certification is a plus.


For New York, NY Only the salary range for this position is USD$210,000.00 - USD$270,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retiremen