Join a leading global firm recognized for its commitment to developing passionate professionals and fostering a culture of continuous growth. We empower you with the training, opportunities, and creative freedom to build your ideal career. At EY, we focus on your potential and provide enriching experiences to help you become the best professional you can be.

This Manager role is within our TMT (Technology, Media & Entertainment, and Telecommunications) Business Consulting Risk practice, specializing in Digital Risk. We help TMT organizations navigate industry convergence, drive growth, and achieve operational excellence while safeguarding their data, brand, and reputation. Our client-centric approach focuses on solving strategic problems and driving long-term value through innovation and technology.

As an AI Risk and Governance Manager, you will be instrumental in identifying, assessing, and mitigating technical risks across Responsible AI dimensions. Your responsibilities include performing quantitative AI model testing, conducting AI red teaming assessments, and designing Responsible AI frameworks. You'll build and maintain automated AI validation pipelines, implement model interpretability solutions, and define AI governance processes for model lifecycle management. This role also involves configuring and monitoring AI systems using MLOps/LLMOps/DevOps practices, collaborating with cybersecurity teams, and translating AI regulations into technical controls. Clear communication of AI risks and business impact to diverse stakeholders is essential.

We are seeking candidates with a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field, coupled with 4-7 years of experience in AI/ML engineering, data science, AI risk, or AI governance. Hands-on experience with production AI/ML systems, a strong understanding of Responsible AI risks (bias, fairness, robustness, explainability, privacy, security), and experience with quantitative AI testing are crucial. Familiarity with MLOps/LLMOps/DevOps and the ability to translate regulatory requirements into technical controls are essential. Excellent communication and collaboration skills are required, along with experience in AI red teaming or safety assessments.