Head of Artificial Intelligence

Responsible AI Lead Purpose The Responsible AI SME is accountable for implementing and advising AI principles (defined in AIMS) across AI portfolio.

The role ensures AI systems are designed, developed, and deployed in alignment with client's values, regulatory requirements, and Responsible AI principles, while enabling safe adoption and business value realization.

Key Accountabilities

Responsible AI Framework & Standards

Maintain Responsible AI principles (along with AI quality & monitoring, discoverability, documentation, AI lineage) in AIMS, related practices and guidance.

Work with legal to establish requirements for fairness, transparency, explainability, accountability, and human oversight.

Develop practical controls and Responsible AI assessment criteria for AI use cases. AI Risk Assessments

Lead Responsible AI reviews for high-risk and business-critical AI solutions - aka AI Steward

Conduct assessments for bias, fairness, explainability, safety, and unintended consequences.

Provide recommendations and mitigation actions to enable safe deployment.

Governance Integration

Embed Responsible AI controls AI lifecycle management processes and governance workflows.

Partner with Governance Operations to operationalize Responsible AI requirements within platforms and tooling.

Support model approval and risk review processes with AI ERC Regulatory & Industry Alignment

Monitor emerging AI standards, and industry best practices.

Advise teams on compliance implications and adoption of regulatory requirements.

Support audit and assurance activities related to Responsible AI.

Education & Adoption

Act as the enterprise Responsible AI thought leader and trusted advisor.

Develop playbooks, guidance, training, and awareness programs.

Promote a culture where Responsible AI enables innovation rather than becoming a barrier to adoption.

Experience

8-12+ years in AI/ML, data science, AI governance, model risk, or technology risk.

Experience evaluating AI risks, fairness, transparency, and explainability.

Experience engaging senior stakeholders and influencing enterprise decisions.

Experience in regulated or complex enterprise environments preferred.

Expertise

Responsible AI and AI ethics

Fairness, explainability, transparency, and AI safety

AI risk management and governance

AI/ML lifecycle and model development practices

Regulatory frameworks (EU AI Act, NIST AI RMF, ISO 42001)

Policy interpretation and control design Behaviors

Demonstrates sound judgment and integrity

Challenges constructively while enabling innovation

Balances business value with ethical considerations

Influences through expertise and credibility

Promote transparency, accountability, and trust