AI Governance Manager

Manager – AI Architect & GovernanceThis is a strategic role for an AI and technology professional who can bridge AI Architecture, AI & Data, Software Engineering, Cybersecurity, Risk Management, Compliance, and Enterprise Governance while enabling the responsible adoption of AI across the organization.The ideal candidate will bring a strong understanding of AI and data technologies, including Python, Java, Data Modeling, Cloud Platforms, Machine Learning, and Agentic AI, together with the ability to establish and operationalize enterprise-wide AI governance frameworks, risk management practices, and incident management processes.Responsibilities Drive the implementation and operationalization of the Enterprise AI Governance Framework, policies, standards, procedures, and controls.Establish and manage AI asset inventories, AI tool inventories, AI system inventories, AI service registries, and AI use-case registries.Lead enterprise-wide AI governance operations, including AI registration, governance monitoring, Shadow AI Management, compliance assurance, and reporting.Drive AI tool onboarding, assessment, whitelisting, and blacklisting in collaboration with Cybersecurity, Risk, Compliance, and IT teams.Define governance controls for AI Agents, Copilots, Agentic AI, and autonomous workflows, including human oversight, accountability, delegation limits, and auditability.Review AI, analytics, and data solution architectures to ensure alignment with enterprise architecture, AI & Data strategy, security, governance, and regulatory standards.Facilitate architecture reviews and provide guidance on scalable, secure, resilient, and compliant AI solutions across enterprise technology environments.Evaluate AI and data architectures involving Python, Java, Data Modeling, cloud platforms, machine learning solutions, and enterprise data platforms to ensure appropriate governance and architectural alignment.Embed governance controls across the AI development lifecycle, including MLOps, model registries, traceability, monitoring, deployment controls, and lifecycle management.Support Responsible AI initiatives covering fairness, explainability, transparency, accountability, bias mitigation, and AI risk management.Conduct AI risk assessments and support AI security governance activities, including AI threat modelling, adversarial testing oversight, and AI risk mitigation.Establish and enhance AI Risk Management and AI Incident Management processes, including risk identification, incident reporting, escalation, investigation, remediation, and lessons learned.Coordinate with Legal, Compliance, Risk, Cybersecurity, and IT teams to ensure AI solutions meet regulatory, privacy, security, and internal policy requirements.Support the implementation, operationalization, sustainability, and continuous improvement of ISO/IEC 42001 AI Management System and certification initiatives.Drive AI governance platforms, model registries, approval workflows, governance automation, audit management, and compliance monitoring capabilities.Develop governance scorecards, executive dashboards, risk indicators, and management reports covering AI risks, compliance, governance performance, incident trends, and AI portfolio health.Support governance reviews of AI vendors, AI-enabled SaaS solutions, foundation models, third-party AI providers, and outsourced AI solutions.Partner with executive stakeholders to continuously enhance the organization's Enterprise AI Governance Program.Provide advisory support to project teams, Data Scientists, Machine Learning Engineers, Data Engineers, Software Engineers, and solution architects on AI architecture, governance, security, risk, and compliance.Promote enterprise-wide awareness and adoption of AI governance standards, Responsible AI practices, and AI governance best practices.Expected Profile Degree in Information Technology, Computer Science, Engineering, Data & Analytics, or a related discipline.5+ years of experience in AI, Data Engineering, Analytics Platforms, MLOps, Technology Architecture, AI Governance, or related technology roles.Strong understanding of AI Governance Frameworks, Responsible AI, AI Risk Management, AI Incident Management, and Model Governance.Knowledge of AI regulatory requirements, privacy regulations, AI security controls, third-party AI risk assessments, and ISO/IEC 42001.Experience managing AI inventories, AI use-case governance, AI governance operating models, and Shadow AI monitoring.Understanding of governance controls for AI Agents, Copilots, Agentic AI, autonomous systems, MLOps Governance, Model Registries, Auditability, and Traceability.Familiarity with AI & Data architecture, machine learning solutions, data engineering, enterprise data platforms, and data lifecycle management.Working knowledge of programming languages such as Python and Java, with an understanding of their application in AI, machine learning, data processing, or enterprise software solutions.Understanding of Data Modeling, data architecture, data quality, data governance, and integration across enterprise data platforms.Hands-on experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).Familiarity with enterprise architecture, software development practices, CI/CD, DevOps, MLOps, and data platform technologies.Ability to collaborate effectively with Machine Learning Engineers, Data Scientists, Data Engineers, and Software Engineering teams to embed governance into AI development and deployment processes.Strong understanding of AI risk assessment, risk mitigation, incident response, governance monitoring, and compliance reporting.Strong leadership, stakeholder management, communication, analytical, and influencing skills.Ability to drive AI governance adoption across diverse business, technology, data, risk, security, and compliance teams.Share your updated CV to careers@talentexpress.lkFollow our LinkedIn page for upcoming 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