About
From bank ledgers to AI agents
Fifteen-plus years architecting data and AI systems — and the business outcomes they drove — across finance, robotics, chemicals, and consulting.
I've spent my career on the seam between the business and the systems that run it. It started at Bank of America, where I built the Finance group's metadata repository and used analytics to review deposit accounts — work that recovered billions of dollars. That was the lesson that has shaped everything since: data is only interesting when it changes a decision.
From there the problems got more physical and more real-time. At Amazon Robotics I built pipelines for the Deployment Engineering team and trained a predictive-maintenance model that cut equipment downtime by 83%. At Evonik Industries I owned the full lifecycle of the data platform behind a niche data science group, and shipped an ML forecasting model that saved $2M in energy costs in a single year.
At Very Technology the job became as much about people as pipelines. As Manager of Data Science and Data Engineering I led teams with an emphasis on product ownership, mentored junior engineers, and drove the integration of LLMs and generative AI into production — including an AI-first system design that lifted user productivity 90% in three weeks and a real-time API platform holding 99.99% uptime at sub-5-second latency. Most recently, at MojoTech, I architect agentic AI and Lakehouse data platforms for clients — building an agentic workforce that reduced operational errors by 30% and bottlenecks by 77%, and enabling 72% growth for a Fortune 500 company.
The throughline is the blend: I can frame the go-to-market case, design the architecture, write the code, and lead the team that keeps it running. That's the kind of Data & AI Architect I am.
What I bring
Business & GTM
I start from the outcome, not the tech. Every pipeline, model, and agent I've built traces back to a number a business cares about — dollars recovered, downtime removed, productivity gained — and I can carry that story from the boardroom to the backend.
Technical Depth
Fifteen years hands-on across the full data lifecycle: streaming and batch pipelines, ML forecasting, real-time IoT platforms, and — most recently — agentic AI and LLM systems on Databricks and AWS.
Leadership & Mentorship
As Manager of Data Science & Data Engineering I led teams around product ownership and scalable delivery, trained and grew junior engineers, and partnered directly with clients to turn ambiguous needs into shipped systems.
Impact, by the numbers
A few outcomes from across the arc — each one a decision the data changed.
recovered in deposit-account reviews at Bank of America
equipment downtime cut with predictive maintenance at Amazon Robotics
saved in one year via an ML energy-forecasting model at Evonik
uptime on a real-time IoT platform (sub-5s latency) at Very
productivity gain in 3 weeks from an AI-first system design
growth enabled for a Fortune 500 via Databricks + AI agents at MojoTech
Professional Experience
Data and AI Architect
MojoTech
Key architect and builder of robust, scalable data pipelines using Databricks and AWS, working directly with clients to understand and deliver on their AI and data needs.
- Designed optimal data architectures that transform raw data into actionable insights, driving critical business decisions
- Architected AI solutions using agents to optimize and automate client workflows and processes
- Integrated and automated data pipelines with Databricks for a Fortune 500 company, enabling AI agents across their work streams and 72% growth
- Built an agentic workforce that automated workflows and managed tasks, reducing operational errors by 30% and bottlenecks by 77%
Manager of Data Science and Data Engineering
Very Technology
Led teams of engineers emphasizing product ownership and scalable solutions integrating LLMs and generative AI.
- Directed the integration of LLMs and Generative AI into existing systems, improving operational efficiency by 80% in 2 months
- Consulted on the design of an AI-first system, increasing data-driven decision-making and user productivity by 90% in 3 weeks
- Developed and deployed an AI agent leveraging a fine-tuned model for real-time guidance, boosting technician efficiency by 22%
- Engineered an event-driven backend enabling advanced marketing strategies, boosting sales profits by 33% in 3 months
- Architected a real-time API platform achieving 99.99% uptime with sub-5s end-to-end latency for IoT data
Senior Data Engineer
Evonik Industries
Created and designed the full lifecycle of data pipelines to support niche Data Science segment to drive decisions.
- Designed and implemented backend system architecture supporting Data Scientists and Analysts
- Implemented machine learning forecasting model for energy consumption, reducing costs by $2M in one year
- Performed data integration, reducing redundancies by 80% and decreasing project overhead by 50%
Data Engineer
Amazon Robotics
Developed and maintained data pipelines used by the Deployment Engineering division of Amazon Robotics.
- Trained predictive modeling algorithm for preventive maintenance, reducing downtime by 83%
- Implemented real-time data processing analytics dashboards for Deployment Engineers
- Worked on IoT optimization of data backend to automate data collection, reducing costs by 10% in one month
Senior Data Engineer/Analyst - AVP
Bank of America
Participated in business reviews to improve data workflows and increase the accountability and usability of the data.
- Designed and implemented the metadata repository for the Finance group within the Bank
- Used business intelligence and analytics tools to perform reviews on deposit accounts, recovering billions of dollars
Let's build something
Based in Providence, RI and open to Data & AI Architect roles. If you have a data or AI problem that needs both strategy and execution, I'd love to hear about it.