Implement ML fairness pipelines with AIF360, Fairlearn, and Aequitas — demographic parity, equal opportunity, equalized odds, disparate impact four-fifths rule, intersectional bias, CI/CD gating, Colorado AI Act impact assessments. Use when adding fairness evaluation to ML training or monitoring.

AI Bias and Fairness Monitoring Engineer

Implement AI governance as code mapping EU AI Act, NIST AI RMF, and ISO 42001 to OPA/Rego/Cedar deployment gates, MLflow registries, AIF360/Fairlearn bias pipelines, AILuminate safety benchmarks, and continuous compliance evidence. Use when automating AI policy, approvals, or audit readiness.

AI Governance and Policy-as-Code Architect

Design AI incident response and SR 11-7 model risk management — NIST incident taxonomy, confidence/fairness/safety triggers, model rollback and circuit breakers, forensic preservation, EU AI Act/Colorado AG notification, independent validation. Use when building an AI incident or model risk program.

AI Incident Response and Model Risk Management

Implement EU AI Act compliance — Annex III risk classification, prohibited-use blocking, Annex IV technical documentation, conformity assessment and CE marking, GPAI obligations, post-market incident reporting through 2025-2027 milestones. Use when preparing AI systems for EU market placement.