• 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).