Your key responsibilities

Client Advisory &

- Delivery

- Lead and deliver AI Governance and Responsible AI engagements, ensuring high quality outcomes within timelines and budgets.

- Advise clients on embedding Responsible AI principles across the AI lifecyclefrom ideation and design to deployment and monitoring.

- Design, assess, and implement AI governance frameworks, policies, standards, and operating models.

- Perform AI use case–level risk assessments, identifying ethical, regulatory, operational, model, data, and technology risks.

- Define risk and control matrices (RCMs) for AI/ML systems aligned to leading frameworks and regulations.

- Test the design and operating effectiveness of AI controls, including governance, model risk, data, security, and monitoring controls.

- Conduct root cause analysis for AI-related issues and incidents and guide clients on practical remediation solutions.

- Develop clear, actionable recommendations and executive ready reports for senior stakeholders.

Responsible AI &

- Technology

- Support clients in operationalizing Responsible AI beyond principles—into processes, controls, tools, and metrics.

- Assess AI/ML systems including traditional ML and Generative AI / Agentic AI applications.

- Guide clients on model risk management, human in the loop controls, explainability, bias mitigation, and monitoring.

- Stay current on evolving AI regulations, standards, and best practices (e.g., EU AI Act, ISO 42001, NIST AI RMF, OECD).

Stakeholder &

- Team Leadership

- Manage day to day client relationships and act as a trusted advisor to senior client stakeholders.

- Lead, mentor, and develop team members; review work products and provide constructive feedback.





- Actively contribute to practice growth, solution development, thought leadership, and go to market initiatives.

Skills and attributes for success

- Strong understanding of AI risks, Responsible AI principles, and AI governance.

- Ability to translate complex AI concepts into practical risk and control solutions.

- Experience performing use case driven risk assessments and control testing.

- Excellent client relationship management and stakeholder engagement skills.

- Explicit, concise, and confident written and verbal communication.

- Strong project management skills, including planning, tracking, and risk management.

- Curious, technology enthusiastic mindset with a passion for continuous learning.

- Structured thinking, problem solving ability, and attention to detail.

To qualify for the role, you must have

- 5+ years of experience in Risk Advisory, AI Risk, Technology Risk, Internal Audit, or AI/ML roles within Big 4 or comparable consulting/technology environments.

- Hands on Responsible AI implementation experience (non negotiable)—either from a risk/governance or AI/ML execution perspective.

- Proven experience in one or more of the following:

- AI Risk Management &
- Governance

- Responsible AI operationalization

- AI/ML model risk assessments

- Root cause analysis and remediation design

- Strong understanding of AI systems, data pipelines, and AI deployment lifecycles.

- Bachelor’s or Master’s degree in Engineering, Computer Science, Risk Management, or a related field.

Good to have

- Professional certifications such as AIGP, ISO 42001, CISA, CISM, CRISC, CISSP, ISO 27001, or similar.

- Working knowledge of Python, ML concepts, or AI tooling to assess implementations effectively.

📌 AI Governance-Manager (Bengaluru)
🏢 EY
📍 Bengaluru