• Regulatory Strategy & Execution: Lead Meta’s regulatory readiness strategy for high-risk AI systems across APAC, LATAM, AMET, proactively preparing the company for global scrutiny around generative models.

• Cross-Functional Leadership: Orchestrated large-scale collaboration across Legal, Policy, Product, Engineering, and Privacy teams to operationalize regulatory obligations—translating legal ambiguity into product-aligned, scalable action plans.

• Product Partnership: Acted as a strategic advisor to product and platform teams, helping balance innovation and speed-to-market with responsible data use and global compliance.

• AI Governance & Responsible Innovation: Played a pivotal role in shaping how Meta assesses and mitigates risk in generative AI systems and sensitive data processing—ensuring transparency, fairness, and accountability are embedded by design.

• Risk Program Design: Built and implemented structured, repeatable processes to assess and respond to regulatory obligations, ensuring timely and accurate engagement with external regulators and internal stakeholders.

• Spearheaded the development of automated, scalable AI dataset review processes, including crawling principles and privacy-sensitive dataset evaluations, supporting responsible AI development and deployment across the company, significantly reducing compliance risk.

• Partnered cross-functionally with Legal, Policy, Product, Engineering, and Research teams to develop and operationalize privacy and risk strategies across AI products, services, and practices.

• Played a key role in shaping the company’s AI privacy strategy by translating legal and regulatory ambiguity into actionable product guidance across high-impact initiatives.

• Led multiple organization-wide risk mitigation initiatives, including the creation of scalable and automated risk review mechanisms that embed privacy and ethical safeguards into product development workflows and increased efficiency from 19% to 63% in 3 months.

• Served as a strategic thought partner on responsible AI governance, helping define principles, practices, and guardrails to align innovation with evolving societal and legal expectations.