AI Governance Operations Lead : Energy Trading

Company: Eaglecliff Recruitment
Apply for the AI Governance Operations Lead : Energy Trading
Location: London
Job Description:

Overview

In this role you will operationalize AI governance across the full lifecycle to enable scalable, auditable control without hindering value delivery. You will work within cross-functional teams to integrate governance into platforms, pipelines, and delivery processes. The position focuses on risk-aware adoption, traceability, and continuous improvement of governance tools and metrics. This is a hands-on, impact-driven opportunity in a world-leading energy trading environment.

Responsibilities

  • Drive end-to-end AI governance across data, development, validation, deployment, monitoring, and retirement stages
  • Embed governance controls into AI/ML platforms, MLOps pipelines, and lifecycle management
  • Own AI governance operations: AI Registry, model/agent inventory, asset tiering, approvals, attestations
  • Automate governance to improve compliance and reduce manual effort while aligning with delivery
  • Ensure traceability, auditability, and transparency of AI assets and decisions
  • Develop governance metrics, dashboards, and KPIs for compliance, adoption, risk, and effectiveness
  • Collaborate with Data & AI, IDSO, Enterprise Architecture, IT Engineering, and CISO to integrate governance into enterprise platforms
  • Support regulatory, audit, and assurance activities with robust evidence management and reporting
  • Drive continuous improvement of governance processes, tooling, and operating models

Key requirements

  • 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
  • Balancing governance rigor with business agility
  • Influencing across organizational boundaries
  • Process optimization and continuous improvement behaviours
  • AI lifecycle management and MLOps
  • Governance process design and automation
  • AI risk, controls, and compliance

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Posted: October 16th, 2026