AI Technology Risk Manager

Empower Retirement, LLC; Kansas; Hybrid; USD 114,000 - 165,000; Full time

Benefits offered by this job

401(k) with company match

Tuition reimbursement

Paid time off

Job summary

Empower Retirement, LLC is seeking an AI Model Risk Manager to identify, assess, validate, and monitor risks associated with machine learning and generative AI models across their lifecycle.

You will work with data science, engineering, product, and risk teams to ensure models are documented, validated, inventoried, monitored, and governed per enterprise standards. A strong background in risk management and AI governance is essential.

Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Risk Management, or a related field.
• Minimum of 7 years of experience in model risk management or AI/ML risk.
• Hands-on experience performing model risk assessments and validation.
• Experience evaluating model methodologies, data, performance metrics, testing approaches, limitations, and ongoing monitoring.
• Strong written and verbal communication skills to translate model risks for technical and non-technical audiences.

Responsibilities

• Execute model risk assessments and validation for machine learning, generative AI, large language models, agentic AI, and other advanced analytical models across the lifecycle.
• Perform independent review and challenge of AI models, including design, assumptions, data suitability, and validation methods.
• Assess model lifecycle governance, identification, risk classification, validation, inventory management, and retirement.
• Develop and maintain model risk metrics, inventories, and governance documentation.
• Communicate conclusions and recommendations to model owners, senior management, and governance forums.

Skills

Model risk assessment

Independent review & challenge

AI/ML risk concepts

Documentation & inventory mgmt

Cross-functional collaboration

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Risk Management, or related field

7+ years of related experience in model risk management or AI risk

Job description

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 Model Risk Manager will identify, assess, validate, and monitor model risks associated with machine learning, generative AI, agentic AI, and other advanced analytical models. This individual contributor will execute model risk assessments and validation activities, perform independent review and challenge, and support the governance of AI and machine learning models throughout their lifecycle. The role will partner closely with data science, engineering, product, business, technology risk, and second-line risk teams to help ensure models are appropriately documented, validated, inventoried, monitored, and governed in accordance with enterprise model risk management standards and risk appetite. The AI Model Risk Manager will translate complex model methodologies, limitations, assumptions, and performance considerations into clear risk conclusions and actionable recommendations for model owners, leadership, and risk governance forums.

What you will do

Execute model risk assessments and validation activities for machine learning, generative AI, large language models, agentic AI, and other advanced analytical models across the model lifecycle, including development, implementation, use, monitoring, change management, and retirement. Perform independent review and challenge of AI and machine learning models, including model design and methodology, intended use, data suitability, training and testing approaches, performance metrics, validation methods, limitations, assumptions, controls, and ongoing monitoring. Assess model conceptual soundness and evaluate whether model development, testing, validation, and monitoring activities are appropriate for the model's intended use and level of risk. Evaluate AI‑specific model risks, including model performance and reliability, bias and fairness, explainability, robustness, data quality, hallucination, drift, misuse, human oversight, and other risks associated with generative and agentic AI. Support the development, review, and ongoing maintenance of model documentation, including model development documentation, validation reports, model risk assessments, monitoring plans, limitations, assumptions, and supporting evidence. Maintain and support the enterprise model inventory to help ensure AI and machine learning models are appropriately identified, classified, risk‑tiered, documented, and governed throughout their lifecycle. Partner with model owners and stakeholders to maintain accurate and complete model inventory records, including ownership, use cases, dependencies, risk classifications, validation status, monitoring requirements, and lifecycle status. Track model validation findings, limitations, remediation activities, exceptions, and other model risk issues and escalating significant concerns in accordance with established risk thresholds. Support ongoing model performance monitoring and periodic review activities, including assessment of model performance, stability, drift, changes in model use, and continued fitness for purpose. Develop and maintain model risk metrics, key risk indicators, inventory reporting, validation status reporting, issue tracking, and other management information used to provide visibility into the organization's AI model risk profile. Prepare clear and concise model risk assessments, validation reports, risk conclusions, and recommendations for model owners, senior management, second‑line risk partners, and governance committees. Support the establishment and ongoing enhancement of AI model risk management policies, standards, procedures, methodologies, templates, controls, and governance processes. Partner with data science, engineering, product, business, technology risk, and enterprise risk teams to identify model risks and establish appropriate controls throughout the AI and machine learning lifecycle. Assess third‑party AI models, foundation models, platforms, and model‑related services to identify model risks and determine appropriate validation, due diligence, documentation, and monitoring requirements. Monitor emerging regulatory guidance, supervisory expectations, industry standards, and leading practices related to model risk management, generative AI, responsible AI, and AI governance. Exercise independent judgment when assessing model risk and challenging model development, validation, implementation, and monitoring practices within established frameworks. Provide model risk recommendations, identify control or documentation gaps, and communicate material findings to the Senior Manager and appropriate risk stakeholders. Contribute analysis and recommendations related to model exceptions, risk acceptances, and remediation plans without holding formal approval authority.

What you will bring

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Risk Management, or a related field.
• A minimum of 7 years of experience in model risk management, model validation, AI/ML risk, quantitative risk, data science, technology risk, or a related discipline.
• Hands‑on experience performing model risk assessments, model validation, or independent review and challenge of machine learning, generative AI, or advanced analytical models.
• Experience evaluating model methodologies, assumptions, data, performance metrics, testing approaches, limitations, and ongoing monitoring.
• Strong understanding of machine learning and AI technologies, including large language models, foundation models, generative AI, model training and evaluation, retrieval‑augmented generation, and agentic AI.
• Understanding of model lifecycle governance, including model identification, risk classification, validation, inventory management, implementation, monitoring, change management, and retirement.
• Experience developing, reviewing, or maintaining model documentation and model inventory information.
• Knowledge of model risk management principles, responsible AI practices, data governance, and AI governance frameworks.
• Familiarity with model performance and validation concepts such as accuracy, stability, robustness, benchmarking, back‑testing, sensitivity analysis, bias and fairness testing, drift monitoring, and model limitations.
• Ability to independently assess and challenge complex quantitative and technical concepts using sound risk judgment.
• Strong written and verbal communication skills, including the ability to translate technical model risks, methodologies, and limitations into clear conclusions for technical and non‑technical audiences.
• Strong analytical skills, attention to detail, and the ability to manage multiple model reviews, documentation requirements, and governance activities simultaneously.
• Proven ability to collaborate effectively across data science, engineering, technology, risk, compliance, and business teams.

What will set you apart

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Risk Management, Business Administration, or a related discipline.
• Direct experience within an established Model Risk Management function performing model validation or independent model review and challenge.
• Experience validating or assessing generative AI, large language models, foundation models, retrieval‑augmented generation systems, or agentic AI solutions.
• Experience managing or supporting an enterprise model inventory, model governance platform, or model lifecycle management process.
• Experience developing model risk reporting, key risk indicators, dashboards, or governance committee materials.
• Experience working in a regulated environment, such as financial services, insurance, healthcare, or fintech.
• Familiarity with regulatory and industry guidance related to model risk and AI, including SR 11‑7/OCC 2011‑12, NIST AI RMF, and other emerging AI risk management standards.
• Relevant professional certification, such as FRM, PRM, CRISC, CISM, CISSP, or an AI/model risk‑related certification.

Working Conditions

• Normal Office Working Conditions
• Flexible Hours

What we offer you

• Medical, dental, vision and life insurance
• Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
• Tuition reimbursement up to $5,250/year
• Business‑casual environment that includes the option to wear jeans
• Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
• Paid volunteer time — 16 hours per calendar year
• Leave of absence programs – including paid parental leave, paid short‑ and long‑term disability, and Family and Medical Leave (FMLA)
• Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

Salary Range

Base Salary Range $114,000.00 - $165,300.00 The salary range above shows the typical minimum to maximum base salary range for this position in the location listed. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation offered may vary from posted hiring range based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer.

Equal Employment Opportunity

Equal opportunity employer • Drug‑free workplace We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.

Remote and Hybrid Positions

For remote and hybrid positions you will be required to provide reliable high‑speed internet with a wired connection as well as a place in your home to work with limited disruption. You must have reliable connectivity from an internet service provider that is fiber, cable or DSL internet. Other necessary computer equipment, will be provided. You may be required to work in the office if you do not have an adequate home work environment and the required internet connection.