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AI Governance Engineer

Evaluation and engineering, a mid-level role

What does AI Governance Engineer do?

Turns policy and risk requirements into technical mechanisms inside development and deployment environments: registries, access control, policy as code, evaluation gates, automated evidence capture and monitoring wired to escalation.

What it decides: Which controls are automated, which need human judgment, and what happens when a gate fails.

The competencies employers name

  • How models work, at a governance depthcore, depth expected

    Explains training, tokens, context windows, embeddings, retrieval and fine-tuning well enough to ask an engineer a precise question and spot weak evidence.

    18 graded topics teach this

  • AI security fundamentalscore, depth expected

    Understands prompt injection, data poisoning, model theft, insecure integrations and excessive agent privileges, and the controls that reduce each.

    17 graded topics teach this

  • Control design and operating-effectiveness testingcore, depth expected

    Maps risks to preventive, detective and corrective controls, then tests design and operation with samples, evidence and defensible findings.

    12 graded topics teach this

  • AI inventory and use-case intakerequired, working knowledge

    Finds every AI system in use, records owner, purpose, data and risk tier, and keeps the record alive as tools change.

    13 graded topics teach this

  • Evidence collection and audit-ready documentationrequired, working knowledge

    Collects, labels and preserves the evidence that a control operated, a decision was made, and a claim can be defended to an auditor or regulator.

    20 graded topics teach this

  • Post-deployment monitoring and drift detectionrequired, working knowledge

    Sets performance metrics, thresholds and review triggers after launch, and treats a model change, a vendor update or new data as a reason to re-check.

    12 graded topics teach this

  • AI evaluation and testing designrequired, working knowledge

    Designs tests for factuality, robustness, fairness, safety and abuse resistance with rubrics, baselines and thresholds, and says what a score misses.

    12 graded topics teach this

  • Agentic AI controls and authorization boundariesrequired, working knowledge

    Governs AI agents that take actions: tool access, least privilege, interruptibility, cascading actions and accountability for what an agent did.

    21 graded topics teach this

  • Data classification, access and retentionrequired, working knowledge

    Classifies information, applies least privilege, sets retention and acceptable-use rules, and controls what may enter a prompt, a log or an embedding.

    19 graded topics teach this

  • AI governance operating model designpreferred, working knowledge

    Designs decision rights, committees, intake, approval tiers and escalation so routine uses move and consequential uses get reviewed.

    20 graded topics teach this

Where it is taught

Counted from the graded topics that teach this role's competencies. Your own path is shorter: it skips what you already cover.

Check your readiness for this role

Add what you already have (optional)
Signed in? Every topic you have passed already counts as proof.

Roles that feed into it

  • Security Engineer
  • Cloud Engineer
  • DevSecOps Engineer
  • MLOps Engineer
  • Privacy Engineer
  • Data Engineer

Where it leads

  • Senior AI Governance Engineer
  • Governance Platform Architect
  • Director of AI Controls Engineering

Backgrounds that reach it fastest

What postings tend to name

Frameworks: NIST AI RMF, ISO/IEC 42001, Google SAIF.

Credentials often listed: Cloud and security credentials, CDPSE, CGRC, CRISC, AIGP. GAGE does not issue these and does not prepare for their exams; the record you earn here is your own graded evidence, which stands beside them.

Questions

What does an AI Governance Engineer build?
The gap between written governance and system behavior: intake workflows tied to the inventory, required metadata, control checks in pipelines, guardrails, and traceability from requirement to evidence.
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