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EY Risk Consulting is seeking a Manager to join its expanding AI Governance and Responsible AI practice. This role is perfect for a technology-focused risk professional passionate about Responsible AI and eager to help organizations integrate trust, ethics, and governance into their AI initiatives. You will act as a crucial link between AI technology, risk management, and governance, driving significant client impact.

In this client-facing role, you will guide global organizations in operationalizing Responsible AI, designing and assessing AI governance frameworks, and evaluating AI/ML risks at a use case level. You will test control effectiveness and help clients transition from high-level AI principles to practical, ground-level implementation, supported by robust risk assessments, root cause analysis, and actionable recommendations.

Key responsibilities include leading AI Governance and Responsible AI engagements, ensuring high-quality delivery within scope and budget. You will advise on embedding Responsible AI principles across the entire AI lifecycle, from design to monitoring, and develop/implement AI governance frameworks, policies, and operating models. Performing AI use case risk assessments, defining risk and control matrices, and testing AI control effectiveness are also core duties. You will conduct root cause analysis for AI issues and provide clients with clear, executive-ready reports and remediation solutions.

This position is ideal for individuals with significant Risk Management experience in Responsible AI or those with hands-on AI/ML experience focused on Responsible AI operationalization. You should possess a strong understanding of AI risks, Responsible AI principles, and AI governance, with the ability to translate complex AI concepts into practical risk and control solutions.

To qualify, you need at least 5 years of experience in Risk Advisory, AI Risk, Technology Risk, Internal Audit, or AI/ML roles within top-tier consulting or technology firms. Proven experience in AI Risk Management & Governance, Responsible AI operationalization, AI/ML model risk assessments, or root cause analysis is mandatory. A solid grasp of AI systems, data pipelines, and AI deployment lifecycles is essential. A Bachelor’s or Master’s degree in Engineering, Computer Science, Risk Management, or a related field is required.