About
From enterprise sales to full-stack AI systems.
I came to computer science after years of working directly with customers and businesses. That changed how I build software: I care about systems that work, workflows that make sense, and products that create measurable leverage.
The short version
A builder with a business past.
Most engineers learn the customer last. I learned them first. Before I wrote production code, I spent years selling and supporting software — sitting across from the people who had to live with it every day. I saw what made software trusted and what made it abandoned.
That experience pulled me toward the other side of the table. I wanted to build the systems, not just represent them. So I went back to school for Computer Science, added a Mathematics minor for the quantitative foundation, and started shipping serious projects instead of waiting for permission.
Today I'm focused on AI-native software: systems where models do real work but humans stay in control. I care about the unglamorous parts — auth, tenancy, migrations, deployment — because that's where production actually lives.
The path
Where I am now — and how I got here
Most recent first. A deliberate transition, not a detour — each step compounds into how I build today.
- NowAI systems
Building AI systems
Agentic CRM — a production-oriented, multi-tenant AI SaaS platform — alongside an AI Construction Estimator and active Honors research. I'm early in the degree but operating far ahead of the typical first-year: designing multi-tenant architecture, auth, billing, and human-in-the-loop AI.
- CurrentComputer Science
Post-Baccalaureate CS at Oregon State University
I returned to school to build the systems I used to sell. 4.0 GPA, Honors College, Mathematics minor, two consecutive Dean's List semesters — and a perfect record in CS coursework to date.
- Several yearsBusiness
Working directly with businesses
I spent years working with companies from small operators to multi-billion-dollar enterprises — close enough to see how software actually gets adopted, where workflows break, and how organizations really make decisions. That perspective is uncommon among engineering students, and it shapes everything I build.
- FoundationFinance
Bachelor of Commerce in Finance
I started in business — markets, capital, and how companies create and measure value. It gave me a way of thinking about leverage and risk that still shapes how I build.
Technical focus
What I'm going deep on
My interests cluster around AI systems and the infrastructure that makes them real and safe.
AI & Systems
- AI Agents
- Human-in-the-loop AI
- LLM workflows
- Applied math
- Quantitative systems
Frontend
- React
- TypeScript
- Vite
- Tailwind CSS
- Next.js
Backend
- FastAPI
- Python
- SQLAlchemy
- Alembic
- REST APIs
Data & Infra
- PostgreSQL
- Redis
- Docker
- Kubernetes
- Job queues
Platform
- Gmail OAuth
- Stripe billing
- JWT / sessions
- RBAC
- Multi-tenancy
What I'm building now
Agentic CRM — a production-oriented, multi-tenant SaaS that reads the inbox, proposes the next action, and keeps a human in control. Alongside it: AI-assisted estimating and Honors research into AI-assisted decision systems.
Where I'm headed
AI-native, high-performance engineering environments — top labs, infrastructure-heavy startups, and teams building real products. I want to work where business judgment and engineering depth are both non-negotiable.
Let's build something serious.
I'm looking for AI-native, high-performance engineering environments where business judgment and engineering execution both matter.