AI Governance Lead
Worldhire Global
Posted by a Verified Recruiter
Industry
Consulting & Advisory
Location
Abu Dhabi, United Arab Emirates
Work mode
On-site
Job type
Full-time
Annual salary
AED 20,000 - AED 30,000 (AED 20 Thousand - AED 30 Thousand)
Minimum experience
8+ years
Posted
5th August, 2026
Required skills
AI/MLData GovernanceTechnology RiskDigital TransformationGovernance FrameworksRisk ManagementStakeholder ManagementExecutive CommunicationRegulatory ComplianceAI Ethics
About the company
WorldHire helps organizations access top global talent through leadership hiring, specialist recruitment, contract staffing, and cross-border search. With KORUM, we are building a trusted talent discovery platform that enables professionals to be discovered discreetly and helps companies find the right expertise faster and more effectively.
About the role
Job Role: AI Governance Lead
Location: Abu Dhabi, UAE
Job Type: On-site
About the Role
We are looking for an AI Governance Lead to anchor organisation 's responsible and scalable use of artificial intelligence. This is a pivotal role that sits at the intersection of strategy, risk, and technology - responsible for leading our Client's AI Maturity Assessment, translating its findings into an actionable governance roadmap, and building the frameworks, policies, and enablement capabilities that will govern how AI is developed, deployed, and monitored across the enterprise.
You will work closely with business units, technology, legal, risk, and data functions to ensure that AI initiatives are trustworthy, compliant, and aligned with both organisational strategy and emerging regulatory requirements.
Key Responsibilities
1. Maturity Assessment (Primary Mandate)
- Lead the end-to-end AI Maturity Assessment - scoping, stakeholder engagement,
evidence gathering, scoring, and results synthesis
- Benchmark the organisation across all maturity dimensions: strategy, culture, data,
technology, talent, and governance
- Translate assessment findings into a prioritised gap analysis and a time-bound AI maturity
improvement roadmap
- Present findings and recommended remediation plans to executive leadership and the
Board AI/Risk Committee
- Establish a repeatable cadence for maturity re-assessment (annual or bi-annual) to track
progress and recalibrate targets
2. AI Governance Framework Development
- Design and implement an enterprise-wide AI Governance Framework covering the full
model lifecycle - from ideation and development through deployment, monitoring, and
decommissioning
- Define AI risk classification tiers and embed proportionate controls for high-risk, medium-
risk, and low-risk AI use cases
- Develop and maintain AI policies, standards, and guidelines (model risk management, bias
& fairness, explainability, data privacy)
- Establish governance bodies including an AI Ethics/Review Board and define terms of
reference, decision rights, and escalation paths
- Embed governance checkpoints into existing SDLC, project management, and
procurement workflows
3. Regulatory Compliance & Risk
- Monitor the evolving AI regulatory landscape (EU AI Act, ISO 42001, NIST AI RMF,
sectoral
regulations) and translate obligations into internal policy and controls
- Maintain an AI inventory / use-case register and ensure all material AI systems have
completed risk assessment and approval workflows
- Partner with Legal, Compliance, and Data Protection teams to ensure AI-related data
governance and privacy obligations are met
- Support internal audit and external regulatory examinations related to AI risk and
Governance
4. Responsible AI & Ethics
- Champion responsible AI principles - fairness, accountability, transparency, safety - and
embed them into toolkits and review processes
- Drive bias detection and mitigation practices across the model development lifecycle
- Develop model explainability standards and ensure high-risk decisions made by AI systems
are auditable and interpretable
- Manage stakeholder concerns and escalations related to AI ethics and algorithmic harm
5. Enablement, Advocacy & Culture
- Build and deliver an AI governance literacy program for business owners, data
scientists,
and technology teams
- Act as a trusted advisor to business units evaluating or scaling AI use cases
- Represent the organization externally at industry forums, regulatory consultations, and
standard-setting bodies
- Report AI governance KPIs and maturity metrics to senior leadership on a quarterly basis
Qualifications & Experience
Essential
- 8+ years of experience spanning AI/ML, data governance, technology risk, or digital
transformation
- Demonstrable experience leading or contributing to an AI or technology maturity
assessment ( CMMI, or equivalent framework)
- Proven track record designing and implementing governance frameworks, policies, or risk management programs in a complex organization
- Strong understanding of the AI model lifecycle and associated risks (bias, drift,
explainability, security)
- Working knowledge of relevant regulations and frameworks: EU AI Act, ISO 42001, NIST ,AI RMF, GDPR.
- Outstanding stakeholder management and executive communication skills - able to
translate technical risk into board-level language
- Experience facilitating cross-functional working groups and governance bodies
Desirable
- Professional certification: GRCP, CDMP, CIPP/E, CISSP, or relevant AI ethics qualification
- Direct experience with client's research methodologies or prior engagement.
- Hands-on experience with AI/ML platforms (Azure ML, AWS Sage Maker, Vertex AI,
Databricks)
- Background in regulated industries: financial services, healthcare, government, or utilities
- Postgraduate degree in Computer Science, Data Science, Law, or a related discipline
Core Skills
•Technical Domain Leadership Interpersonal
- • AI/ML lifecycle model risk management
- • Executive communication board reporting client's AI Maturity framework
- • Stakeholder management influence AI governance policy design
- • Cross-functional facilitation
- Regulatory compliance (EU AI Act, GDPR)
- • Strategic thinking prioritization, Responsible AI ethics frameworks
- • Change management culture building
- Data governance privacy
- • Program project management
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