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AI Governance Jobs

AI governance professionals build and run the internal programs that keep AI development accountable - model review processes, responsible-AI frameworks, risk registers, and the policies that govern how a company builds and deploys AI systems. The role sits at the intersection of engineering, legal, and policy.

33 live AI Governance roles across the AI employers we track - updated hourly, apply directly.

AI Governance roles are rare: 33 live right now. Get the new ones every Monday.

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Latest AI Governance roles

Governance is an internal process function

AI governance is inward-facing work. The job is to build the machinery a company applies to itself: model review gates before a system ships, an inventory of AI use cases, a risk register that someone actually maintains, internal standards for documentation and testing, and an escalation path for when a review fails. Success looks like decisions that are recorded and repeatable, not like a research result or a shipped feature.

The reporting line matters when you read a posting. Governance usually sits under legal, risk, or a chief privacy or trust office rather than under engineering, and the day-to-day is convening people who do not report to you. That makes the core skills facilitation, writing, and knowing enough about model development to ask the right question, rather than building models. Engineers moving into governance often find the change of leverage harder than the change of subject.

Two forces created most of these openings. Frontier developers published responsible-scaling and preparedness style frameworks that commit them to specific evaluations and thresholds before deploying more capable models, and those commitments need staff to run. Separately, enterprise buyers began sending AI-specific due-diligence questionnaires to their vendors, so any company shipping AI features now needs someone who can answer them with evidence rather than with assurances.

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Frequently asked questions

Are companies hiring for AI Governance right now?
We are tracking 33 live AI Governance roles across the AI companies we monitor, updated hourly. Each listing links straight to the employer's own application page.
How is AI governance different from AI compliance?
Governance builds the internal system - review gates, standards, inventories, and decision records - and applies whether or not a law covers the product. Compliance maps that system onto specific external obligations such as the EU AI Act or ISO/IEC 42001 and produces the evidence an auditor or regulator would ask for. Smaller teams often combine both in a single role.
What does an AI governance program actually produce?
Typical artifacts are an inventory of AI use cases with risk tiers, a documented review process with defined gates and owners, model and system documentation templates, an approved-tools policy for internal AI use, incident and escalation procedures, and a decision record showing why each system was allowed to ship.
Do AI governance roles sit in engineering or in legal?
Most sit outside engineering, under legal, risk, privacy, or a trust and safety organization, because the function needs independence from the teams it reviews. Postings still expect technical fluency: enough understanding of training data, evaluation, and deployment to challenge an engineering team's assessment without writing the model code.

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