Governance IT Data Engineer ( M/F/D )

We are looking for an experienced Governance Operations Lead to help operationalise AI governance requirements across a large enterprise environment.
About the Role:
As Governance Operations Lead, you will play a key role in embedding AI governance into the end-to-end AI lifecycle. You will ensure governance controls are integrated into AI/ML platforms, lifecycle processes and delivery pipelines, enabling scalable, automated and auditable governance while supporting AI adoption and value creation.
Key Responsibilities:
Implement AI governance processes across the full AI lifecycle, including data, development, validation, deployment, monitoring and retirement.
Embed governance controls into AI/ML platforms, MLOps pipelines and lifecycle management processes.
Manage AI governance operations, including AI registries, model and agent inventories, asset tiering, approvals and attestations.
Drive automation to reduce manual governance activities and improve compliance.
Ensure traceability, transparency and auditability of AI assets, models and decisions.
Develop governance metrics, dashboards and KPIs covering compliance, adoption, risk and effectiveness.
Collaborate with Data & AI, Enterprise Architecture, IT Engineering, CISO and other technology teams.
Support regulatory, audit and assurance activities through effective evidence management and reporting.
Continuously improve governance processes, tooling and operating models.
8–12+ years of experience in AI/ML, technology operations, governance, risk, digital transformation or a related field.
Proven experience implementing enterprise governance processes and operating models.
Experience working with AI/ML platforms, MLOps, DevSecOps or data platforms.
Demonstrated ability to operationalise controls and drive adoption across complex organisations.
Expertise:
AI lifecycle management and MLOps
AI governance, risk, controls and compliance
Governance process design and automation
Data and model management platforms
Metrics, reporting and operational excellence
Process optimisation and continuous improvement

Employment type
Full-time

Work arrangement
Hybrid