Los Angeles, California, United States
Engineering Leader in Applied ML and Generative AI, focused on building scalable LLM/RAG systems and ML infrastructure. Delivered production AI platforms serving 25k+ enterprise users and driving $20M+ in measurable impact. Proven track record leading high-performing teams across operations, advertising, and cloud AI domains. Expert in ML deployment, optimization, experimentation, and AWS-native architectures.
In September 2026, my partner Adib Khosravi and I bought Ninedot, a Providence agency that’s been doing digital marketing, web design, and SEO for 25 years. The team and client relationships that built the business are still here. We want to keep it that way. As CEO, much of my focus is on engineering and our AI roadmap. Right now, that means building DotAI, our SEO platform designed to help clients understand what’s moving their rankings. Adib leads operations and client relationships. If you’re a Ninedot client or run a small business and are tired of SEO that feels like a black box, I’d like to hear from you.
Led product and business strategy for an AI-driven metabolic health platform (iOS/Android, CGM integrations, provider portal), managing engineering, data, and clinical teams to deliver secure, real-time personalized insights and expand access through partnerships and insurance coverage.
Led a 10+ member team designing and deploying RAG-based Generative AI solutions that scaled to 25,000+ users across Amazon Operations.
Scaled and led a 20+ person cross-functional organization of Scientists, Data Engineers, and Software Engineers delivering AMC-based targeting solutions.
Led strategic AI/ML consulting engagements for enterprise AWS customers, delivering production-scale ML systems, advising executives on AI strategy, and guiding cross-functional teams to translate business requirements into deployable AWS solutions.
Developed models to measure the effectiveness of Snapchat’s advertising campaigns, managed end-to-end Dataflow and Spark job execution, and evaluated ad performance using data-driven methods.
Served as Technical Lead for Transaction Modeling, leading a team of software engineers and data scientists and reporting directly to the CTO. Developed machine learning models to detect potentially fraudulent transactions and threats, designing classification models with a very low false negative rate to identify high-velocity, high-volume transactions, resulting in significant cost savings for the company.