EY Consulting is seeking a Senior Consultant specializing in AI Risk and Governance within the TMT sector. This role focuses on transforming businesses through people, technology, and innovation, addressing client's most strategic problems. The position is based in Mumbai and involves driving long-term value by solving complex risk-related challenges.

As part of the TMT (Technology, Media & Entertainment, and Telecommunications) practice, you will help companies navigate industry convergence, enhance competitiveness, and develop agile strategies for growth. The focus is on creating compelling employee and customer experiences, protecting data and brand reputation, and enabling M&A strategies to drive value and mitigate risk.

Key responsibilities include identifying, assessing, and mitigating technical risks across Responsible AI dimensions like bias, fairness, robustness, explainability, privacy, and security. You will perform quantitative AI model testing, conduct AI red teaming assessments, and design/implement Responsible AI frameworks. Building and maintaining automated AI validation, monitoring, and alerting pipelines is crucial. You will also implement model interpretability solutions, define and operationalize RAI metrics, and design AI governance processes for model lifecycle management.

Further responsibilities involve configuring and monitoring AI systems using MLOps/LLMOps/DevOps practices, partnering with cybersecurity and fraud teams, and translating AI regulations into technical requirements. Communicating AI risks and business impact to stakeholders and developing technical documentation and training materials are also key aspects of this role.

To qualify, candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field. A minimum of 3 to 7 years of experience in AI/ML engineering, data science, AI risk, or AI governance roles is required. Hands-on experience building, testing, deploying, and monitoring AI/ML systems in production is essential.

Strong understanding of Responsible AI risks, experience with quantitative AI testing, and working knowledge of MLOps/LLMOps/DevOps are necessary. The ability to translate regulatory requirements into technical controls and strong communication skills are vital. Experience with AI red teaming and collaborating with cybersecurity or enterprise risk teams is also beneficial.