AI Governance

2–4 years of experience in AI/ML governance, data governance, or a similar analyst role

Technical literacy — you don’t need to write code day-to-day, but you should be able to read and critically assess ML pipeline documentation, CI/CD workflows, model cards and vendor technical profiles; you can ask the right questions and spot what’s missing

Governance-engineering translation — able to take a policy or regulatory requirement and work with engineering teams to define how it gets enforced technically — whether through guardrails, monitoring, logging or platform configuration

Governance and risk awareness — familiarity with AI concepts such as bias, drift, explainability, model cards, performance benchmarks; awareness of the EU AI Act is a strong plus

Requirement formulation — able to translate regulatory or policy language into structured, testable control requirements that engineering and data science teams can act on

Strong documentation skills — clear, structured written communication; comfortable producing control frameworks, checklists and audit-ready records