AI Compliance Jobs

A role that translates AI laws and standards into policies, controls, and documentation, owning conformity, technical files, audits, and regulator relationships for an organization's AI.

Most prominently the EU AI Act, plus emerging US state and federal AI rules and existing sector regulation that now applies to AI systems.

A control library mapped to more than one framework at once, so a single test can satisfy the EU AI Act, ISO/IEC 42001 and an internal policy together. A model or use-case registry. A findings tracker with owners and due dates wired into engineering's queue. An evidence repository collected on a schedule rather than reconstructed before an audit. And a policy library with version control and attestation tracking.

Reading a regulation and turning it into a control someone can actually perform, then testing whether they did. Around that: writing that survives legal review, evidence discipline, enough technical literacy to argue with a data scientist about what a model actually does, stakeholder management with people who see compliance as overhead, and enough platform skill to configure a workflow instead of filing a ticket and waiting.

A requirement arrives, from a regulator, a customer contract, or a framework the company adopted. It gets mapped to controls that already exist, and the gaps become work with owners and dates. Controls are tested on a schedule, testing produces evidence and findings, findings are remediated or accepted with a documented rationale, and the loop is reported upward. Then the requirement changes and it runs again.

Most people arrive from compliance, internal audit, privacy or security rather than from machine learning. The fastest credible move is to take one regulation, build a control matrix mapping its clauses to testable controls with owners, test procedures and evidence requirements, and be able to walk someone through it. Pair that with the AIGP or an existing GRC credential and you are competitive for analyst and specialist openings.