New York, New York, United States
I was brought in to answer a question Meta hadn't fully solved yet: how do you take the work of evaluating hundreds of privacy safeguards — digging through documentation, traversing millions of lines of code, assessing controls, building monitors — and make it something AI can do? As the Subject Matter Expert and Lead for Meta's AI Pod initiative, I built that system. The automation pipeline we developed eliminated ~85% of the engineer effort previously required to stand up and validate safeguard monitors across Facebook, Instagram, WhatsApp, Threads, Messenger, and Oculus. What used to take days now takes hours. What used to require a team now scales. The work sits at an intersection most people don't occupy: deep knowledge of FTC external assessor demands and evaluation frameworks, hands-on AI/LLM agent architecture, and the ability to translate between regulators, lawyers, engineers, and data scientists in the same conversation. Before Meta I spent a decade doing similar translation work in financial crime — AML/BSA compliance at Bank of China, global audit analytics at Crane Co., risk analytics at PwC. The throughline has always been the same: take high-stakes regulatory requirements and build automated systems that satisfy them at scale. I'm particularly interested in how AI can make compliance and Trust & Safety enforcement faster, more precise, and less dependent on manual review cycles. The problems are hard, the stakes are real, and the tooling is finally catching up. 📍 New York, NY | Open to conversations about AI-driven policy enforcement, Trust & Safety, and privacy compliance at scale.
Selected as Subject Matter Expert to lead the Privacy workstream of Meta's AI Pod initiative — a companywide program to automate controls across Privacy, Security, and Integrity. Own end-to-end AI automation for all privacy controls and safeguards across Facebook, Instagram, WhatsApp, Threads, Messenger, and Oculus. 🔹 Architected an AI automation pipeline that eliminated ~85% of engineer effort previously required to evaluate safeguard documentation, traverse the Meta codebase, assess controls, and build daily efficacy monitors. 🔹 Built LLM agents that autonomously navigate Meta's codebase, evaluate safeguard implementations, auto-generate code diffs, and produce monitor configurations — compressing review cycles from days to hours. 🔹 Designed and deployed 50+ automated Trust & Safety safeguard monitors for Anti-Scraping and Rate-Limiting controls — serving as primary FTC consent order audit evidence and eliminating 100+ engineer hours per audit cycle. 🔹 Developed deep expertise in FTC external assessor demands and evaluation frameworks, translating assessor requirements directly into AI-driven enforcement architecture that proactively closes coverage gaps before audit cycles. 🔹 Spearheaded safeguard maturation for Incident Management, closing critical assessor-identified policy gaps and reducing manual audit remediation by 30%. 🔹 Partnered with privacy engineering and Trust & Safety teams to embed AI-powered monitoring into new product launches, ensuring compliance-by-design across generative AI initiatives. 🔹 Built real-time data pipelines and dashboards (Presto/SQL, Unidash) to measure safeguard health and surface enforcement coverage gaps before assessor review cycles. Skills: AI Agents · LLMs · Trust & Safety · Privacy Compliance · FTC Consent Order · Python · SQL · Prompt Engineering
Here's the reformatted Crane Co. blurb in the same style: Automation & Data Analytics Lead, Global Internal Audit Crane Co. · Jan 2020 – Aug 2022 · Stamford, CT Led the digital and analytical transformation of the global internal audit function at Crane Co., a 150+ year industrial manufacturer with business segments spanning Aerospace & Electronics, Engineered Materials, Payment & Merchandising Technology, Fluid Handling, and Controls. Owned the roadmap for building Crane's first global audit analytics and business intelligence capability from the ground up. 🔹 Built and scaled the global data analytics and business intelligence team, applying Alteryx, SQL, Python, and Power BI across 90% of audits — establishing analytics as a core capability of the audit function rather than a niche skill. 🔹 Developed Crane's first continuous T&E monitoring dashboard, uncovering fraud and expense abuse and providing leadership with real-time visibility; adopted directly by corporate executives. 🔹 Designed continuous audit monitoring and risk assessment dashboards in Alteryx and Power BI, enabling proactive identification of risk across business segments and replacing point-in-time reviews with always-on visibility. 🔹 Architected dedicated databases for ERP data extracts, streamlining audit scoping and execution and giving auditors direct access to clean, structured population data. 🔹 Built advanced audit analyses in SQL and Python to perform full-population testing, support ad-hoc audits, guide senior management decisions, and drive risk assessment for the annual audit plan. 🔹 Deployed RPA to automate organization-wide processes, reducing process errors and freeing audit and finance teams to focus on higher-value work. 🔹 Trained and mentored 20+ auditors as automation champions, building self-service dashboards and workflows that flagged critical risks across Crane's global operations.
Responsible for leading an offshore team in the space of Audit Transformation Analytics, Internal Audit Analytics. Data Transformation - Used SQL, ACL, and Excel to automate revenue fraud testing (SAS99) for major ERP systems including SAP, Oracle, PeopleSoft, NetSuite, and Workday. Account Management - Managed over 15 clients at a time across several industries including investment funds, REITS, and consumer packaged goods and services. Revenue Recognition Standard - Develop process flow and business requirement documents for public companies to facilitate changing to the new accounting revenue recognition standards. Leasing Standard - Helped developed lease extraction machine learning platform used by public companies to extract required accounting information in order to conform to the new leasing standard. Trained employees in the new leasing standard requirements for new clients.