Led org-level engineering initiatives across privacy, observability, and metadata platforms, serving as a technical owner for correctness-critical infrastructure and partnering closely with Infra, Legal, and Product teams to strengthen Meta’s data governance and operational reliability.

Designed and drove Meta’s Privacy Unified Taxonomy, a company-wide metadata abstraction that standardized data semantics across thousands of services. Built end-to-end automation pipelines to propagate taxonomy into code, datasets, and infra systems, eliminating large-scale manual tagging and saving 100+ FTE-years annually.

Built core privacy compliance platforms that power policy assignment, data-flow verification, and remediation at scale. Reduced privacy review turnaround time by 70%+, unblocked compliant launches, and enabled nine-figure business impact across multiple product surfaces.

Developed internal AI- and automation-driven platforms to accelerate privacy and infra workflows, turning previously manual, review-heavy processes into paved paths adopted by multiple engineering orgs and significantly improving end-to-end response speed.

Modernized nationwide case and inquiry management systems supporting large-scale, compliance-sensitive workflows, improving platform reliability, maintainability, and end-user productivity.

Defined service boundaries, schemas, and release processes, partnering closely with QA and security teams to support federal compliance and audit requirements while enabling safer, faster deployments.

Supported the HealthIT.gov platform by building features, maintaining multi-site architecture, and improving content publishing workflows for policy teams.

Migrated the platform to updated infrastructure and improved deployment stability through containerization and environment modernization.