Job Summary

Manager-TMT-Business Consulting Risk-CNS - Risk - Digital Risk - Mumbai

Your 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 using internal testing toolkits and external evaluation platforms.
- Conduct AI red teaming assessments (manual and automated) to identify 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 to support internal audits, regulatory reviews, and stakeholder trust.
- Define and operationalize RAI metrics, dashboards, and monitoring systems for ongoing compliance and risk tracking.
- Design 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 to address AI driven security, scam, and abuse risks.
- Translate AI regulations, laws, and ethical standards into technical requirements, controls, and engineering guardrails.
- Communicate AI risks, controls, and business impact clearly to both technical and non technical stakeholders.
- Develop technical documentation, standards,



and training materials to support organization wide Responsible AI adoption.

Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
- 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.
- Strong understanding of Responsible AI risks, including bias, fairness, robustness, explainability, privacy, and security.
- Experience with quantitative AI testing, validation frameworks, and evaluation platforms.
- Working knowledge of MLOps / LLMOps / DevOps and CI/CD workflows for ML systems.
- Ability to translate regulatory and governance requirements into actionable technical controls.
- Solid communication skills, including experience working with cross functional or client facing teams.
- Experience with AI red teaming, adversarial testing, or safety assessments.
- Experience collaborating with cybersecurity, fraud, or enterprise risk teams.
- Familiarity with agentic AI systems (e.g., autonomous agents, tool use, multi step reasoning) and associated risks.
- Preferred Certifications: Azure AI Engineer Associate / AWS Machine Learning - Specialty / Google Professional Machine Learning Engineer / CISSP / CCSP / CRISC

Experience

- Artificial Intelligence (3+ years)

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Manager (Mumbai)
🏢 EY
📍 Mumbai