New York City Metropolitan Area
AI & Agentic Systems
Designed and built components of Meta's agentic AI investigation platform, enabling investigators to conduct complex investigations through natural language interaction with AI agents
Architected Sub-Investigations — a parallel agent framework that lets AI investigations to fan out complex investigative work to multiple concurrent AI agents, dramatically reducing investigation time
Built Agentic Case Self-Summarization — an LLM-powered system that auto-generates investigation summaries from investigative data
Drove LLM capacity planning for AI-powered integrity tools, including GPU capacity estimation and usage modeling
Core contributor to Investigative platform used by integrity teams across the organization
Designed and built Investigative API infrastructure: logging pipelines, reliability metrics, and automation endpoints supporting millions of case operations