I help companies make AI useful in real operations.
For 20 years I worked inside large companies — banks, payments, manufacturing, telecom, energy. I learned how to make technology useful in real operations, and how to make it survive the chaos of real business.
Projects fail for the same reason: the company or the team isn't ready. The data's scattered, the workflow lives in someone's head, and nobody asks the people who do the job every day. So most of my job is understanding how the work really happens before deciding what to build. Sometimes the answer is AI. More often it's plain automation, merging of two datasets, or a system and integration that should have existed years ago.
Building it isn't the hard part anymore. Anyone can sit down with AI and have working code by the end of the day. Owning it is the hard part — running it in production, fixing it when it breaks, keeping it alive while the business shifts around it. That's the part most people would rather hand off, and it's the part I want.
What I'm building with
- Python, Go, TypeScript
- PostgreSQL, Redis, Kafka
- Docker, Kubernetes
- AWS, GCP, Azure
- Terraform, CloudFormation
- Observability & monitoring
- Anthropic & OpenAI APIs
- Vector databases
- RAG & agent architectures
- Spark, dbt, Airflow
- Event streaming & CDC
- Real-time analytics
Experience
AI automation for US Industrial Base. Hands-on engineering with their leaders — process and workflow automation.
Built an AI platform that cut inter-agency friction, and brought monthly infrastructure cost from $20K down to $1K.
Rebuilt the data team so it shipped four times faster, and built a real-time platform that analyzed over $1B in transactions.
Built a data lake and predictive analytics on AWS for 14 manufacturing sites. Chief architect of the operations platform and self-serve analytics.
Built an IoT platform monitoring thousands of machines, and pushed edge computing for farming, manufacturing, and logistics customers.
Principal data engineering architect (through EY) for a next-gen data platform.
Led onshore and offshore teams digitizing supply chain tracking and product quality with operations leaders.
Led onshore and offshore teams on an enterprise data warehouse and reporting initiative.
Rebuilt the Asset Management data warehouse to handle both near-real-time and large batch processing.
Built the team, architecture, and data infrastructure for the MBS portfolio and led the compliance reporting build-out.
Built CDS, MBS, and IRS-specific VAR, M2M, and P&L models, and a platform (AFRICA) for the Investment Bank.
Integration engineer for the Duke Energy–Cinergy merger.