Senior Consultant - AI Risk and Governance (TMT, Digital Risk)

About the role

EY is hiring a Senior Consultant for its Business Consulting Risk practice, focused on TMT (Technology, Media & Entertainment) and digital risk, based in Mumbai. The role covers technical aspects of AI risk and governance, helping clients identify, assess and mitigate risks in responsible AI, including bias, fairness, robustness, explainability, privacy and model/data security.

Key responsibilities

• Identify, assess and mitigate technical risks across Responsible AI dimensions, including bias, fairness, robustness, explainability, privacy and model/data security.
• Perform quantitative AI model testing with internal toolkits and external evaluation platforms.
• Conduct AI red teaming assessments (manual and automated) to find safety, security, misuse and adversarial risks.
• Design and implement Responsible AI frameworks for bias detection, fairness evaluation, explainability and robustness.
• Build and maintain automated AI validation, monitoring and alerting pipelines across development and production environments.
• Implement model interpretability and explainability solutions for internal audits, regulatory reviews and stakeholder trust.
• Define RAI metrics, dashboards and monitoring systems, and operationalize AI governance processes for model lifecycle management, approvals and change control.
• Configure, deploy and monitor AI systems in cloud and on-premise environments using MLOps, LLMOps and DevOps practices.
• Partner with cybersecurity, fraud and information security teams on AI-driven security, scam and abuse risks.
• Translate AI regulations, laws and ethical standards into technical controls and guardrails, and communicate risks to technical and non-technical stakeholders.
• Develop technical documentation, standards and training materials for Responsible AI adoption.

Required profile

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science or a related field; MBA or MCA also listed as acceptable.
• 4-7 years of experience in AI/ML engineering, data science, AI risk or AI governance roles.
• Hands-on experience building, testing, deploying and monitoring AI/ML systems in production.
• Experience with AI red teaming, adversarial testing or safety assessments, and collaboration with cybersecurity, fraud or enterprise risk teams.
• Familiarity with agentic AI systems and their risks.

Required skills

• Strong understanding of Responsible AI risks (bias, fairness, robustness, explainability, privacy, security).
• Quantitative AI testing, validation frameworks and evaluation platforms.
• Working knowledge of MLOps, LLMOps, DevOps and CI/CD for ML systems.
• Preferred certifications: Azure AI Engineer Associate, AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, CISSP, CCSP, CRISC.