Technical Architect | Staff Software Engineer
Building and scaling enterprise products and platforms from the ground up.
- 14+ years across three organizations — the last 8 building and scaling one commerce platform from 1 retailer to 90+ at peak
- Served 416M+ delivery predictions a year at sub-150ms P99 latency, plus 60M+ orders, 80M+ shipments, and 680M+ tracking events
- Own the end-to-end architecture of a 10+ module SaaS platform — domain model, event-driven backbone, and multi-tenant design
- Lead a 15-engineer cross-functional team, and personally built the four production AI copilots this site's own AI assistant is modeled on
A live demo of my agentic AI work
This assistant is built on my production RAG stack.
Same retrieval and agentic patterns shipped for customers, answering live from my real work instead of a script. Ask about the architecture, the scale, or how this assistant itself is built.
The evidence
Four stories behind those numbers
Situation, what I did, what it was worth: the short version here, the full account on the Blog page.
Ownership & closing power
Using Architecture to Close a Four-Year Enterprise Opportunity
A 4-year-pursued enterprise account finally closed, because of a 2-month build, not a bigger pitch deck.
Business impact from technical depth
Finding $100K/Month in Hidden Carrier Costs From a Customer's Own Data
A deep dive into one customer's own shipping data uncovered well over $100K a month in avoidable cost.
Product thinking, not just engineering
Turning Post-Purchase Pages Into a Revenue and Retention Channel
A tracking page, a notification system, and a coupon engine: a 5-9% conversion lift and a 95% drop in support calls, from pages that used to have neither purpose.
Agentic AI, shipped
Turning Institutional Knowledge Into a Tool, Not a Wiki Page
Four RAG and agentic copilots, all live in production for internal teams, turning documentation, past resolutions, and static pages into something you can just ask.
Architecture case studies
Three systems, three different architectural problems
Prediction at scale, event-driven reliability, and applied AI — the three technical problems every conversation about this platform eventually gets to. Full case studies, including the decisions and tradeoffs behind each, live on the Architecture page.
Core stack
Architecture & Design
Messaging & Streaming
Databases & Data Engineering
AWS & Cloud-Native
Extending the architecture with AI
Four AI copilots are live in production for internal teams — tracking status, configuration guidance, onboarding steps for a new customer, and root-cause analysis that matches a new support issue against ones already solved. The chat assistant on this page runs on that same retrieval-and-generation approach right now.
Read how the copilots work →