Partner with second line enterprise risk and application teams to define, document, and build ML and AI governance policy, processes, controls, and governance tools.
Execute technology risk assessments for Machine Learning, Generative AI, and advanced analytics solutions across design, development, deployment, and monitoring phases.
Perform independent risk review and challenge of AI/ML models, including data sourcing, training approaches, validation methods, and ongoing performance monitoring.
Support the establishment and ongoing execution of AI/ML risk governance, standards, and control frameworks aligned to the Enterprise Risk Appetite Framework.
Partner with engineering, data science, product, and business teams to identify risks and embed effective controls into AI/ML systems and processes.
Assess and support management of third-party and vendor risks associated with AI platforms, tools, models, and data sources.
Prepare clear 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 within established frameworks, provide control feedback and issue identification to the Senior Manager, and escalate significant risks or control gaps in accordance with defined thresholds.
Contribute analysis and recommendations to risk acceptance decisions (without formal approval authority).

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, Risk Management, or a related field
Master’s degree (or relevant experience in lieu of advanced education)
4 to 6 years of experience in technology risk, model risk management, cybersecurity, data risk, or related disciplines
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 working in regulated environments (for example, financial services, insurance, healthcare, or fintech)
Experience partnering with engineering and data science teams in fast-paced technology environments
Strong understanding of AI/ML technologies, including LLMs and 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
Highly analytical, detail-oriented, and comfortable working with ambiguity
Proven ability to collaborate effectively across technology, risk, and business teams.

Benefits

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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningGenerative AIrisk assessmentsmodel risk managementdata governancecloud-based infrastructureAI/ML technologiesmodel trainingvalidation methodsperformance monitoring

Soft Skills

independent judgmentanalytical skillsdetail-orientedcommunication skillscollaborationability to work with ambiguitytechnical risk assessmentrecommendation formulationcontrol feedbackissue identification