Join EY's expanding AI Governance and Responsible AI practice as a Manager, where you'll champion trust and ethics in AI journeys for global organizations. This client-facing role is perfect for technology-savvy risk professionals passionate about embedding Responsible AI principles into AI lifecycles.

Leverage your expertise to operationalize Responsible AI, design governance frameworks, assess AI/ML risks, and test control effectiveness. You'll guide clients from high-level principles to practical, on-the-ground implementation, backed by robust risk assessments and actionable insights.

As a Manager, you will lead AI Governance and Responsible AI engagements, ensuring high-quality client delivery. Advise on embedding AI principles across the entire AI lifecycle, from design to monitoring.

Key responsibilities include designing and implementing AI governance frameworks, conducting AI use-case risk assessments, defining risk and control matrices, and testing AI control effectiveness. You will also perform root cause analysis for AI-related issues and provide clear, executive-ready reports and recommendations. Support clients in operationalizing Responsible AI, assess AI/ML systems including Generative AI, and guide on model risk management, bias mitigation, and explainability, while staying current with evolving AI regulations.

To excel in this role, you need 5+ years of experience in Risk Advisory, AI Risk, Technology Risk, Internal Audit, or AI/ML roles, preferably within Big 4 or comparable consulting/technology firms. Hands-on experience in Responsible AI implementation is essential, either from a risk/governance or AI/ML execution standpoint.

Proven expertise in AI Risk Management & Governance, Responsible AI operationalization, AI/ML model risk assessments, or root cause analysis and remediation design is required. A strong understanding of AI systems, data pipelines, and AI deployment lifecycles is crucial. A Bachelor’s or Master’s degree in Engineering, Computer Science, Risk Management, or a related field is necessary. Professional certifications and working knowledge of Python, ML concepts, or AI tooling are advantageous.