EY Consulting is seeking a Senior Consultant to join our Digital Risk team in Mumbai. This role focuses on transforming businesses through people, technology, and innovation, solving strategic problems and driving long-term value for clients. You will be instrumental in managing risks within the Technology, Media & Entertainment, and Telecommunications (TMT) sector, contributing to a better working world.

This opportunity offers a chance to work with leading organizations, navigating industry convergence and driving agile corporate strategies. You will help clients create exceptional employee and customer experiences, protect their data and reputation, and pursue M&A strategies that build future powerhouses in the technology revolution.

Your key responsibilities will involve identifying, assessing, and mitigating technical risks across Responsible AI dimensions such as bias, fairness, robustness, explainability, privacy, and security. You will perform quantitative AI model testing, conduct AI red teaming assessments, and design Responsible AI frameworks.

Additionally, you will build and maintain automated AI validation, monitoring, and alerting pipelines. Implementing model interpretability solutions and operationalizing AI governance processes are crucial. You will also configure and monitor AI systems using MLOps, LLMOps, and DevOps practices, collaborating with cybersecurity and fraud teams to address AI-driven risks.

Furthermore, you will translate AI regulations into technical requirements, communicate AI risks and business impact to stakeholders, and develop technical documentation and training materials for broader Responsible AI adoption.

We are looking for candidates with a Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field. A minimum of 4–7 years of experience in AI/ML engineering, data science, AI risk, or AI governance roles is required.

Hands-on experience with building, testing, deploying, and monitoring AI/ML systems in production is essential. You should possess a strong understanding of Responsible AI risks and experience with quantitative AI testing, validation frameworks, and evaluation platforms.

Working knowledge of MLOps/LLMOps/DevOps and CI/CD workflows for ML systems is necessary. Excellent communication skills and experience working with cross-functional or client-facing teams are vital. Familiarity with AI red teaming and agentic AI systems is also beneficial.