AI PRODUCT & ENGINEERING LEADERSHIP
From the first prototype to millions of interactions. I build the teams, platforms, and operating discipline that make ambitious AI deliver.
DIRECTOR, DATA SCIENCE · PRUDENTIAL FINANCIAL DRAPER, UTAH
Annual AI interactions
AVA · Service & ClaimsEnterprise AI initiatives
Originated, built, or advisedDirectly attributed AUM
Retirement Location PlannerDirect reports / cross-functional
Leadership that connects disciplines01 / AN INTERACTIVE BODY OF WORK
Ask a question. Follow the evidence. An AI guide can query this public portfolio and bring the relevant connections into focus.
CONNECTED, NOT COLLECTED
Select a node to see the work, capabilities, and outcomes behind it.
NOT A SCRIPTED DEMO When connected, a real model chooses the portfolio tools. Tool inputs, outputs, and sources remain inspectable. Graph exploration works independently of the AI connection.
02 / SELECTED WORK
A portfolio spanning scaled service platforms, customer-facing generative AI, and the next layer of organizational intelligence.
AI at the scale of daily operations.
Conceived and own the primary daily AI platform for Service and Claims. Product strategy, delivery, and continuous optimization—not an isolated proof of concept.
From individual agents to shared expertise.
A persistent agent harness with context-inheriting subagents, dynamic skills, and peer-to-peer networking. An executive-sponsored pilot exploring bottom-up knowledge capture and executable expertise exchange.
Analytics that can take the next step.
Production agentic analytics combining autonomous analysis loops, code execution, and hosted applications. A practical shift from answering questions to producing usable analytical work.
Customer value. Measurable growth.
Conceived and prototyped before ChatGPT, then launched into production in April 2023. Personalized retirement recommendations and dashboards translated generative AI into a measurable customer proposition.
Turning heterogeneous data into structured intelligence.
Independently designed and shipped a multi-agent knowledge-extraction and ontology platform in approximately one month. Staged extraction and validation, deterministic graph construction, and a company pivot around the resulting platform.
03 / HOW I LEAD
Closing that distance takes more than a model. It takes product judgment, technical depth, and an organization equipped to deliver.
The full career story ↗Roadmap, budget, vendors, risk, and delivery. Connect the technical choices to the operating model and the business outcome.
Six direct reports. 50–70 cross-functional contributors. Founded U.S. Business GenAI Labs and authored Prudential’s first Responsible AI standards.
A physics foundation, quantitative engineering at Point72, and production machine learning at AT&T. Executive ownership grounded in hands-on systems judgment.
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