AI Governance Leader

We are looking for an AI Governance Leader to establish and lead the organizations AI governance framework. This role ensures that Artificial Intelligence Generative AI Machine Learning automation and advanced analytics initiatives are aligned with business objectives regulatory requirements security standards and ethical principles.

The role serves as the central authority for AI governance risk management compliance and policy oversight across enterprise technology infrastructure operations service delivery security cloud platforms and data analytics functions.

Job Responsibilities:

AI Governance Strategy & Framework

• Develop and maintain the enterprise AI Governance Strategy policies standards and operating model.
  

• Define governance structures decision-making forums accountability frameworks and escalation processes for AI initiatives.
  

• Establish governance across the AI lifecycle covering ideation design development deployment monitoring and retirement.
  

• Create governance controls that support the responsible adoption of AI-enabled operational services automation platforms and intelligent service management capabilities.
  

• Ensure alignment between AI governance objectives and broader enterprise technology transformation and business strategies.
  

Responsible AI & Risk Management

• Establish policies and controls to ensure AI solutions operate in a responsible transparent fair and secure manner.
  

• Lead AI risk assessments covering operational security compliance legal financial reputational and model risks.
  

• Define governance processes for model validation approval performance monitoring and ongoing oversight.
  

• Develop controls for AI explainability accountability auditability and traceability.
  

• Ensure appropriate management of risks associated with autonomous operations intelligent automation and AI-driven decision-making.
  

Compliance Security & Regulatory Oversight

• Partner with security privacy legal and compliance teams to ensure AI solutions comply with applicable regulations and organizational policies.
  

• Establish governance controls for data privacy information security access management and data protection within AI ecosystems.
  

• Define audit and reporting mechanisms to demonstrate compliance and control effectiveness.
  

• Support internal and external audits involving AI automation analytics and operational platforms.
  

• Ensure AI governance practices are integrated with existing enterprise risk and security frameworks.
  

Data Governance & Quality Management

• Define governance requirements for data quality lineage ownership retention and stewardship supporting AI solutions.
  

• Establish standards for the use of operational business and infrastructure data in AI models.
  

• Ensure governance controls exist to manage data bias quality issues and inappropriate use of enterprise information.
  

• Collaborate with data platform teams to maintain trusted and governed data environments.
  

• Monitor adherence to data governance policies across AI and analytics initiatives.
  

AI Operations & Performance Oversight

• Define governance metrics KPIs and reporting standards for AI-enabled services and automation initiatives.
  

• Establish monitoring and review processes to measure AI effectiveness business value realisation service quality and risk exposure.
  

• Oversee governance of predictive analytics intelligent automation AIOps and self-service solutions.
  

• Facilitate periodic reviews of AI performance and governance maturity.
  

• Drive continuous improvement initiatives based on operational insights and governance findings.
  

Vendor & Third-Party Governance

• Establish governance processes for evaluating and managing AI-related technologies vendors partners and service providers.
  

• Define due diligence contractual governance and risk assessment requirements for third-party AI solutions.
  

• Monitor compliance with governance standards across vendors participating in AI-enabled service delivery models.
  

• Support enterprise vendor consolidation and governance initiatives by ensuring appropriate controls over externally provided AI capabilities.
  

Stakeholder Engagement & Governance Leadership

• Chair or lead AI Governance Boards Review Committees and Risk Forums.
  

• Provide executive reporting on AI risks compliance posture value realisation and governance effectiveness.
  

• Educate business and technology stakeholders on responsible AI practices and governance requirements.
  

• Promote a culture of accountability transparency and responsible AI adoption throughout the organization.
  

• Serve as a trusted advisor to senior executives on AI-related governance and strategic decisions.
  

Requirements

The ideal candidate should meet the following requirements:

Education:

• Bachelors degree in Computer Science Information Technology Data Science Engineering Law Risk Management or a related discipline.
  

Professional Experience:

• 12 years of experience in enterprise technology governance risk management compliance security architecture or operational leadership roles.
  

• 5 years of experience governing AI analytics automation digital transformation or emerging technology programs.
  

• Proven experience developing enterprise governance frameworks policies standards and operating models.
  

• Experience working within complex multi-vendor large-scale managed services or enterprise environments.
  

• Demonstrated success influencing executive stakeholders and leading cross-functional governance initiatives.
  

Technical & Governance Expertise:

• Strong understanding of Artificial Intelligence Machine Learning Generative AI Predictive Analytics Intelligent Automation and AIOps.
  

• Deep knowledge of AI governance principles model risk management and AI lifecycle controls.
  

• Experience implementing governance frameworks for enterprise technology platforms and cloud environments.
  

• Understanding of data governance data quality management metadata management and data protection controls.
  

• Familiarity with IT Service Management operational governance and enterprise transformation programs.
  

• Knowledge of cloud platforms enterprise monitoring analytics platforms and automation toolsets commonly used in modern infrastructure environments.
  

• Understanding of security controls privacy requirements and regulatory considerations affecting AI solutions.
  

Leadership & Business Skills:

• Strong executive communication and stakeholder management capabilities.
  

• Ability to balance innovation objectives with governance and risk management requirements.
  

• Excellent facilitation negotiation and decision-making skills.
  

• Proven ability to establish enterprise-wide governance programs and drive organizational adoption.
  

• Strong analytical and problem-solving capabilities.
  

• Experience leading governance councils steering committees and executive review boards.
  

Preferred Qualifications:

• Relevant governance risk compliance or AI governance certifications.
  

Required Skills:

We are looking for an AI Governance Leader to establish and lead the organizations AI governance framework. This role ensures that Artificial Intelligence Generative AI Machine Learning automation and advanced analytics initiatives are aligned with business objectives regulatory requirements security standards and ethical principles.

The role serves as the central authority for AI governance risk management compliance and policy oversight across enterprise technology infrastructure operations service delivery security cloud platforms and data analytics functions.

Job Responsibilities:

AI Governance Strategy & Framework

• Develop and maintain the enterprise AI Governance Strategy policies standards and operating model.
  

• Define governance structures decision-making forums accountability frameworks and escalation processes for AI initiatives.
  

• Establish governance across the AI lifecycle covering ideation design development deployment monitoring and retirement.
  

• Create governance controls that support the responsible adoption of AI-enabled operational services automation platforms and intelligent service management capabilities.
  

• Ensure alignment between AI governance objectives and broader enterprise technology transformation and business strategies.
  

Responsible AI & Risk Management

• Establish policies and controls to ensure AI solutions operate in a responsible transparent fair and secure manner.
  

• Lead AI risk assessments covering operational security compliance legal financial reputational and model risks.
  

• Define governance processes for model validation approval performance monitoring and ongoing oversight.
  

• Develop controls for AI explainability accountability auditability and traceability.
  

• Ensure appropriate management of risks associated with autonomous operations intelligent automation and AI-driven decision-making.
  

Compliance Security & Regulatory Oversight

• Partner with security privacy legal and compliance teams to ensure AI solutions comply with applicable regulations and organizational policies.
  

• Establish governance controls for data privacy information security access management and data protection within AI ecosystems.
  

• Define audit and reporting mechanisms to demonstrate compliance and control effectiveness.
  

• Support internal and external audits involving AI automation analytics and operational platforms.
  

• Ensure AI governance practices are integrated with existing enterprise risk and security frameworks.
  

Data Governance & Quality Management

• Define governance requirements for data quality lineage ownership retention and stewardship supporting AI solutions.
  

• Establish standards for the use of operational business and infrastructure data in AI models.
  

• Ensure governance controls exist to manage data bias quality issues and inappropriate use of enterprise information.
  

• Collaborate with data platform teams to maintain trusted and governed data environments.
  

• Monitor adherence to data governance policies across AI and analytics initiatives.
  

AI Operations & Performance Oversight

• Define governance metrics KPIs and reporting standards for AI-enabled services and automation initiatives.
  

• Establish monitoring and review processes to measure AI effectiveness business value realisation service quality and risk exposure.
  

• Oversee governance of predictive analytics intelligent automation AIOps and self-service solutions.
  

• Facilitate periodic reviews of AI performance and governance maturity.
  

• Drive continuous improvement initiatives based on operational insights and governance findings.
  

Vendor & Third-Party Governance

• Establish governance processes for evaluating and managing AI-related technologies vendors partners and service providers.
  

• Define due diligence contractual governance and risk assessment requirements for third-party AI solutions.
  

• Monitor compliance with governance standards across vendors participating in AI-enabled service delivery models.
  

• Support enterprise vendor consolidation and governance initiatives by ensuring appropriate controls over externally provided AI capabilities.
  

Stakeholder Engagement & Governance Leadership

• Chair or lead AI Governance Boards Review Committees and Risk Forums.
  

• Provide executive reporting on AI risks compliance posture value realisation and governance effectiveness.
  

• Educate business and technology stakeholders on responsible AI practices and governance requirements.
  

• Promote a culture of accountability transparency and responsible AI adoption throughout the organization.
  

• Serve as a trusted advisor to senior executives on AI-related governance and strategic decisions.
  

Requirements

The ideal candidate should meet the following requirements:

Education:

• Bachelors degree in Computer Science Information Technology Data Science Engineering Law Risk Management or a related discipline.
  

Professional Experience:

• 12 years of experience in enterprise technology governance risk management compliance security architecture or operational leadership roles.
  

• 5 years of experience governing AI analytics automation digital transformation or emerging technology programs.
  

• Proven experience developing enterprise governance frameworks policies standards and operating models.
  

• Experience working within complex multi-vendor large-scale managed services or enterprise environments.
  

• Demonstrated success influencing executive stakeholders and leading cross-functional governance initiatives.
  

Technical & Governance Expertise:

• Strong understanding of Artificial Intelligence Machine Learning Generative AI Predictive Analytics Intelligent Automation and AIOps.
  

• Deep knowledge of AI governance principles model risk management and AI lifecycle controls.
  

• Experience implementing governance frameworks for enterprise technology platforms and cloud environments.
  

• Understanding of data governance data quality management metadata management and data protection controls.
  

• Familiarity with IT Service Management operational governance and enterprise transformation programs.
  

• Knowledge of cloud platforms enterprise monitoring analytics platforms and automation toolsets commonly used in modern infrastructure environments.
  

• Understanding of security controls privacy requirements and regulatory considerations affecting AI solutions.
  

Leadership & Business Skills:

• Strong executive communication and stakeholder management capabilities.
  

• Ability to balance innovation objectives with governance and risk management requirements.
  

• Excellent facilitation negotiation and decision-making skills.
  

• Proven ability to establish enterprise-wide governance programs and drive organizational adoption.
  

• Strong analytical and problem-solving capabilities.
  

• Experience leading governance councils steering committees and executive review boards.
  

Preferred Qualifications:

• Relevant governance risk compliance or AI governance certifications.
  

Required Education:

Bachelors degree in Computer Science Information Technology Data Science Engineering Law Risk Management or a related discipline.

Employment Type : Full Time
Experience: years
Vacancy: 1