AI Governance-Manager

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.
• Clear, 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.