AI Technology Risk Manager

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.

The AI Technology Risk Manager will identify, assess, and manage technology risks associated with machine learning, generative AI, and emerging technologies. This individual contributor will execute risk assessments, provide independent review and challenge, and partner with technology, data science, product, and business teams to help ensure AI and machine learning solutions are designed and operated in a safe, ethical, and compliant manner. The role will translate complex technical risks into clear, actionable insights and embed effective controls throughout the AI and machine learning lifecycle.

What you will do:

• Partner with second-line enterprise risk and application teams to define, document, and build machine learning and AI governance policies, processes, controls, and governance tools.
• Execute technology risk assessments for machine learning, generative AI, and advanced analytics solutions across the design, development, deployment, and monitoring phases.
• Perform independent risk review and challenge of AI and machine learning models, including data sourcing, training approaches, validation methods, and ongoing performance monitoring.
• Support the establishment and ongoing execution of AI and machine learning risk governance, standards, and control frameworks aligned with the Enterprise Risk Appetite Framework.
• Partner with engineering, data science, product, and business teams to identify risks and embed effective controls into AI and machine learning systems and processes.
• Assess and support the management of third-party and vendor risks associated with AI platforms, tools, models, and data sources.
• Prepare clear and concise risk documentation, assessments, and recommendations for review by the Senior Manager and risk governance forums.
• Monitor emerging regulatory guidance, industry standards, and best practices related to AI, model risk, and responsible AI.
• Contribute to risk metrics, reporting, and materials presented to leadership, risk committees, and second-line partners.
• Exercise independent judgment when conducting technology and AI and machine learning risk assessments within established frameworks.
• Provide risk recommendations, control feedback, and issue identification to the Senior Manager, Technology Risk.
• Escalate significant risks, control gaps, or issues in accordance with defined risk thresholds.
• Contribute analysis and recommendations related to risk acceptances without holding formal approval authority.

What you will bring:

• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, Risk Management, or a related field.
• A minimum of 7 years of experience in technology risk, model risk management, cybersecurity, data risk, or a related discipline.
• Hands-on experience performing risk assessments for machine learning and/or generative AI solutions.
• Solid understanding of model and agent development on cloud-based infrastructure.
• Experience partnering with engineering and data science teams in fast-paced technology environments.
• Strong understanding of AI and machine learning technologies, including large language models, model training, validation, and deployment.
• Knowledge of responsible AI principles, model risk management, and data governance practices.
• Ability to independently assess and challenge complex technical risks using sound judgment.
• Strong written and verbal communication skills, including the ability to explain technical risks to non-technical audiences.
• Strong analytical skills, attention to detail, and comfort working with ambiguity.<