Governance Operations Lead – AI

Exciting opportunity for an AI Governance Operations Lead to join a World Leading Energy Trading company on a long-term contract basis in London.

Purpose

The Governance Operations Lead is responsible for operationalizing AIMS governance requirements (AI ownership, AI tiering, AI lifecycle, AI operating model, etc) across the company by embedding governance controls into AI lifecycle management processes, platforms, and project delivery pipelines. The role enables scalable, automated, and auditable governance while balancing AI value realization, adoption, and risk management.

Key Accountabilities

• Drive implementation of AI governance processes across the end-to-end AI lifecycle (data, development, validation, deployment, monitoring, and retirement)
• Embed governance controls into AI/ML platforms, MLOps pipelines, and AI lifecycle management
• Own AI governance operations including AI Registry, model/agent inventory, AI asset tiering, approvals, attestations
• Establish governance automation to improve compliance, reduce manual effort, and avoid policy based governance that is disconnected from delivery
• Ensure traceability, auditability, and transparency of AI assets, models, and decisions
• Develop governance metrics, dashboards, and KPIs to measure compliance, adoption, risk, and effectiveness
• Partner with Data & AI, IDSO, Enterprise Architecture, IT Engineering, and CISO teams to integrate governance into enterprise platforms
• Support regulatory, audit, and assurance activities through robust evidence management and reporting
• Drive continuous improvement of governance processes, tooling, and operating models.

Experience

• 8-12+ years in AI/ML, technology operations, governance, risk, or digital transformation.
• Experience implementing enterprise governance processes and operating models.
• Experience with AI/ML platforms, MLOps, DevSecOps, or data platforms.
• Proven track record of operationalizing controls and driving enterprise adoption.

Expertise

• AI lifecycle management and MLOps
• Governance process design and automation
• AI risk, controls, and compliance
• Data and model management platforms
• Metrics, reporting, and operational excellence
• Process optimization and continuous improvement behaviours
• Systems thinker with a strong operational mindset
• Balances governance rigor with business agility
• Drives simplification and automation
• Influences across organizational boundaries
• Focuses on outcomes, scalability, and adoption

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