AI Risk Oversight, Director
BlackRock is hiring an AI Risk Oversight, Director in New York, United States. It pays $210k a year and Level rates it ; you can apply on BlackRock.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include AI agents.
- Level classifies it as an executive role.
- Level lists 244 other open roles at BlackRock.
- The role was posted in the last few days.
AI in this role
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.
Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
Guidance on AI use for candidates
At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
About BlackRock
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.
To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.
BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.
BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com. All requests are treated in line with our privacy policy.
BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.How we rate this
AI Risk Oversight, Director at BlackRock rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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Skills and AI tools this role asks for
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- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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