Applied AI Engineer · Production ML Systems · Geospatial Intelligence · GCP · New York
I build AI systems that work in production. My focus is GCP-native data architecture, geospatial intelligence pipelines, and retrieval-augmented generation systems for enterprise. Currently in the Google Startups Accelerator building IDist ®, a global asset management platform. Looking for the right team doing complex, meaningful work.
My technical focus is GCP-native AI systems. I build geospatial intelligence pipelines with PostGIS and BigQuery, RAG architectures with Vertex AI and Gemini, and production APIs on FastAPI and Cloud Run. The systems I build are designed to be maintained, audited, and trusted by people who aren't engineers.
I've shipped four production platforms in the last two years: IDist ® (global asset management, Google Startups Accelerator), LH-PVI (insurance document intelligence, 70% processing reduction), NYCID (NYC property dossiers across 12 municipal data sources), and Vera VB (voice biometric identity infrastructure, private beta).
The VERA framework and The Proof Economy essay came from this work. They're my attempt to formalize what I've learned about building trustworthy AI systems and what verification infrastructure means for the next decade.
I've built businesses in music, design, real estate, and AI. I understand enterprise buyers, procurement cycles, and the gap between a demo and a product people trust with real decisions.
Not just API calls. Full-stack GCP with IAM, Cloud Run, BigQuery, Vertex AI, Firestore, and Cloud Functions working together as production infrastructure.
Property, insurance, infrastructure, and logistics domains where location is the core data layer. PostGIS, BigQuery GIS, and spatial reasoning pipelines.
I build for maintainability, not just functionality. Structured output validation, audit trails, error handling, and observability from day one.
Every output has provenance. Every decision is traceable. VERA is the formal expression of this practice, but the mindset runs through everything I build.
This is the most transformative technology of my lifetime, and I love building with it. That's why I'm always exploring new projects, new architectures, and new ways to apply AI to real problems. The energy comes from the work itself.
I'm grateful to be part of the Google Startups Accelerator as a solo founder. Their support while building IDist ® has been invaluable. But building from zero isn't new for me. I've started companies across music, interior design, and manufacturing in New York City. Each one sharpened how I think about constraints, coordination, and creating opportunity for talented people.
That experience shapes how I approach engineering. I understand what it takes to move from prototype to production, not just technically but operationally. I've navigated procurement, compliance, multi-stakeholder coordination, and real budget constraints.
I'm looking for a team working on complex, high-stakes problems where I can contribute real depth in production AI systems while learning from strong engineers and product thinkers. I do my best work when the problems are hard, the standards are high, and the people are good.
I started in music production and design. Those industries teach you quickly that tools matter less than the taste, judgment, and problem framing you bring to them. That sensibility carried directly into software engineering.
The thread across everything I've built is a focus on the gap between what systems promise and what they actually deliver. The Proof Economy essay is my thesis on where this leads: when AI capability is abundant, the scarce resource is verified quality. VERA is the methodology for building it.
If something here resonates, or if you want to push back on any of it, I'm always up for a good conversation.