Lead Operational and AI Risk Manager

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Operational and AI Risk Manager based in the United States. This role combines operational risk management, data analytics, model oversight, and responsible AI within a non-financial risk environment. You will lead complex analytical and risk oversight initiatives that support regulatory priorities and strategic business objectives. The position works closely with Risk, Technology, Compliance, Audit, and business stakeholders to identify risks and develop practical solutions. You will independently navigate ambiguous problems, translate complex information into actionable recommendations, and influence stakeholders without direct authority. A key focus is the independent validation of AI and LLM-enabled models, including structured evaluation and responsible AI practices. The role is fully remote within the United States and offers broad exposure to evolving risk, fraud, analytics, and AI priorities. \n Accountabilities: - Analyze data from multiple sources to identify trends, anomalies, emerging risks, and areas requiring management attention, while developing clear reports, dashboards, metrics, and presentations for risk leaders and senior stakeholders. - Assess business processes, operational activities, policies, controls, monitoring practices, and organizational changes to determine whether risks are appropriately managed and safeguards are operating as intended. - Lead cross-functional initiatives involving Risk, Technology, Compliance, Audit, and business teams, supporting regulatory commitments, remediation programs, strategic priorities, and other complex risk initiatives.

- Provide independent oversight of models and analytical tools, evaluating model design, inputs, outputs, performance, limitations, monitoring practices, and documentation through a risk-based approach. - Lead the independent validation of an AI- and LLM-enabled regulatory model, applying model governance and validation methodologies while serving as a subject matter expert in responsible AI practices. - Apply structured LLM evaluation techniques such as benchmark testing, output consistency checks, adversarial prompting, and bias assessment to evaluate model reliability and suitability for regulatory use. - Prepare clear validation and risk documentation covering methodologies, findings, limitations, conclusions, and recommended actions in formats suitable for regulatory review. - Use AI tools in day-to-day risk activities, including research, analysis, and drafting, while identifying opportunities to improve the efficiency and quality of risk oversight through AI-enabled workflows. - Assess emerging AI technologies and associated risks and contribute to governance considerations and practical implementation guidance as AI capabilities continue to evolve. - Analyze fraud prevention, detection, monitoring, and response practices using available data, identifying trends, gaps, emerging concerns, and opportunities to strengthen program effectiveness. - Support regulatory examinations, internal reviews, remediation efforts, and time-sensitive risk initiatives while independently managing complex assignments from problem definition through recommendations and implementation support. - Build productive relationships across business, technology, compliance, audit, and risk functions, challenging assumptions constructively and influencing stakeholders through expertise, sound judgment, and practical problem solving. Requirements: - Bachelor’s degree in business, finance, economics, mathematics, statistics, data analytics, information systems, risk management, or a related field, with at least 7 years of relevant experience in risk management, fraud, model oversight, data analytics, or a related discipline.