Summary
Aaron Horvitz is a Senior GenAI Systems Engineer with nine years of experience building production-grade AI and analytics systems across enterprise and government settings. He architects scalable LLM and RAG pipelines and vector database integrations for multi-cloud deployments at PwC, after leading applied-statistics and LLM-driven projects at the IRS that automated audit analytics and enabled searchable access to over a million pages of tax guidance. Comfortable from low-level ETL and time-series forecasting to deploying agentic workflows, he pairs rigorous statistical training (MS in Statistical Data Science) with hands-on software engineering to replace ad-hoc scripts with industrial-grade platforms. His background includes building computer vision and real-time forecasting solutions for industry, founding a recruiting tech startup, and serving as a US Army Ranger—experience that surfaces in his discipline for reliable, auditable systems. Notably, he has practical experience operationalizing LLMs for high-stakes, privacy-sensitive workflows, blending classical ML with modern generative techniques.
9 years of coding experience
10 years of employment as a software developer
BS Economics (CFA Candidate while pursuing coursework), BS Economics (CFA Candidate while pursuing coursework) at University of Houston
Passed June 2010 Level I Exam, Passed June 2010 Level I Exam at CFA Program
Master of Science - MS Statistical Data Science Department of Statistics, Master of Science - MS Statistical Data Science Department of Statistics at Texas A&M University