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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