Compliance Program Build-Out

Before touching any policy document, a comprehensive AWS security assessment mapped current infrastructure state against documented requirements. Findings were prioritized by severity and translated into 35 actionable tickets with clear ownership assignments, priority ratings, and SLA timelines. A systematic infrastructure verification methodology was then developed using AWS CLI commands to validate every policy claim: S3 encryption audits confirmed AES-256 across all production buckets, RDS verification checked encryption, KMS associations, and Multi-AZ deployment across 10 database instances, and replication testing definitively confirmed that no cross-region replication existed - directly contradicting the Backup Policy. TLS configuration testing confirmed A+ SSL Labs ratings with TLS 1.3 on production domains. This verification uncovered the critical false geographic redundancy claim that would have been an immediate audit finding.

With infrastructure reality documented, the policy renewal addressed 25+ policies with 5 requiring substantive updates. The Data Retention Policy underwent a major rewrite from V1.0 to V2.1 - streamlined from 6 to 4 pages by removing sections duplicating backup and asset management policies, while adding AI/ML data retention requirements aligned with NIST AI RMF and the EU AI Act, plus HR data schedules meeting FLSA, EEOC, and IRS requirements. The data sanitization standard was updated from withdrawn NIST SP 800-88 Rev. 1 to Rev. 2 with IEEE 2883:2022 as a supplementary standard. The Backup Policy was corrected to accurately document Multi-AZ deployment within a single region, replacing the false cross-region claim - with the change log noting verification via AWS CLI.

For multi-framework control mapping, SOC 2 controls were brought to all-green status with zero open findings. The NIST AI RMF alignment required 12+ entirely new controls and processes: Data Protection Impact Assessments, AI committee governance structures, fairness and bias evaluation procedures, opt-out mechanisms for automated decisions, environmental impact assessments, AI-specific risk tracking, and responsible AI training modules. All policy updates were coordinated across VP Engineering, CTO, HR, and IT Operations with targeted review assignments. A critical process decision determined which updates required staff re-acknowledgement versus silent publication - preventing unnecessary disruption while maintaining compliance. Of 35 remediation tickets, 20 were closed during the engagement with the remainder tracked with documented remediation timelines.