Risk Compliance Manager - AI

Job Title: AI Governance Lead (Responsible AI, Risk & Policy)

Role Overview

The AI Governance Lead is responsible for establishing and operationalizing the organisation's AI governance, risk management, and ethical use frameworks. This role ensures that all AI and GenAI initiatives comply with applicable regulations, align with internal policies, uphold data protection and ethical standards, and are deployed responsibly at scale. The AI Governance Lead acts as the practical owner of the company's Responsible AI strategy, guiding teams through the development, assessment, and safe deployment of AI solutions.

Key Responsibilities

1. Regulatory, Legal & Ethical Oversight

• Review and interpret relevant AI regulations, standards, and legal frameworks across jurisdictions.
• Monitor evolving global AI governance and responsible AI requirements and translate them into internal guidelines.
• Lead ethical assessments of AI use cases to ensure alignment with corporate values, human rights, and fairness principles.

2. AI Risk Management

• Define and implement a comprehensive AI risk assessment methodology.
• Build and maintain an AI Risk Assessment Tool aligned with enterprise risk and compliance processes.
• Establish technical and procedural guardrails on data protection, model quality, and data sufficiency.

3. Governance Frameworks, Policies & Standards

• Design and implement an AI ethics review process with clear decision gates.
• Draft, socialize, and obtain approval for organizational GenAI and broader AI governance policies.
• Define AI deployment principles, lifecycle controls, and compliance checkpoints.
• Develop AI solution deployment checklists and operating standards to guide teams through responsible rollout.
• Create technical foundation guidelines for AI governance, including documentation expectations, auditability, transparency, and controls.

4. AI Use Case & Portfolio Governance

• Build and maintain an enterprise AI use case backlog with evaluation criteria.
• Develop and implement an AI initiative assessment framework for impact, risk, and feasibility scoring.
• Support business teams in assessing AI readiness and selecting responsible solutions.

5. Strategic Leadership & Knowledge Transfer

• Serve as the practical lead for the overall AI Governance strategy and roadmap.
• Partner with Legal, Risk, Compliance, Data, Security, Engineering, and business teams to embed responsible AI practices.
• Lead knowledge-sharing, training, and upskilling on responsible AI topics across the organisation.
• Guide teams in adapting global guidelines into local operational processes.

Qualifications & Experience

Required

• Bachelor's degree in Law, Data/Computer Science, Information Governance, Compliance, or related fields.
• 612 years of experience in Risk, Compliance, Data Governance, Cybersecurity, or AI/Tech Governance roles.
• Demonstrated experience implementing governance frameworks, policies, or risk assessment methodologies.
• Strong understanding of AI/ML systems, including data lifecycle, model risks, and evaluation considerations.
• Familiarity with data protection laws and AI regulatory environments (e.g., EU AI Act, GDPR, ISO/IEC 42001, NIST AI RMF).
• Excellent stakeholder management and communication skills.

Preferred

• Experience with Responsible AI programs or AI ethics frameworks.
• Background in technology audit, digital policy, or enterprise architecture.
• Certification in data protection, risk management, AI governance, or compliance (e.g., CIPP, ISO RMF, AI Ethics certifications).
• Ability to work in cross-functional environments and influence senior stakeholders.

Key Competencies

• Governance & Risk Expertise understands regulatory, legal, and risk disciplines.
• Technical Fluency comfortable evaluating AI/ML concepts and risks.
• Policy Development able to translate complex requirements into actionable policies and guardrails.
• Ethical Judgment ensures fairness, transparency, and responsible outcomes.
• Strategic Thinking shapes long-term AI governance direction.
• Stakeholder Leadership influences without direct authority.
• Communication & Training simplifies complex topics for diverse audiences.

Success Measures

• Organisation-wide adoption of AI governance frameworks and processes.
• Compliance with internal policies and external regulatory requirements.
• Effective risk mitigation for AI solutions and use cases.
• Increased responsible AI maturity across teams and business units.
• Clear documentation and auditability of AI systems and decisions.