Security & Compliance

When dealing with sensitive technical domains, data handling isn’t just about accuracy; it’s about trust. I design workflows that respect privacy, handle PII, and maintain auditability from ingestion through retrieval.

My Approach

• PII & Secret Filtering – Automated redaction and filtering during preprocessing to strip sensitive data before it reaches embeddings or indexes.

• Data Lineage & Audit Logs – Every dataset and model run is tracked with manifests, hashes, and version metadata for compliance.

• Access Controls – Role-based restrictions on who can ingest, query, or modify data pipelines.

• License & Source Compliance – Clear tracking of where data came from, including license terms and usage rights.

Advancing Further

I continue to expand methodology toward:

• Integrated Policy Engines – automatic enforcement of retention rules and access policies.

• Zero-Trust Data Handling – encryption and access validation applied at every stage of the pipeline.

• Compliance Automation – structured reporting that maps pipeline activity to standards like NIST, DoD STIGs, or SOC 2.

Why It Matters

Security and compliance can’t be an afterthought. By embedding these controls directly into the AI pipeline, I ensure the systems I design are responsible, auditable, and enterprise-ready from day one.