I build production AI systems.
I also build the teams that ship them.

Twenty years in technology. Fifteen shipping mission-critical systems. Current focus: large language models, agentic AI, and the engineering enablement that lets a team move twice as fast next quarter.

About

I am a Principal Software Engineer based in California. Most recently I led engineering on a 0-to-1 multi-tenant AI communication insights platform. Now looking for the next interesting project and a long-term team. I want to solve hard problems people care about.

What I have shipped

  • Production AI built on Graph RAG, LLMs, and agentic workflows
  • Event-driven, serverless systems on AWS and Azure
  • A React-based instant claim payout system that moved well over $1M
  • Confidential compute on Intel SGX for medical AI use cases
  • Multi-sensor data capture for Reality Labs at Meta

How I work with teams

  • Six years as a people manager. Five-plus as a technical lead
  • Grew an architecture practice from four to eleven engineers in two years
  • Hundreds of engineers and aspiring engineers mentored over the years. A few examples:
    • Mentoring a security professional through the move to independent consulting
    • Helped a senior engineer retool for the AI era
    • Coached a new engineer into becoming a celebrated lead
    • Introduced a teenager to game development. They went on to major in computer science
  • Repeat speaker at high school career days

Where I show up publicly

What I am working on

Three problem shapes I keep coming back to:

  • Production AI systems. Graph RAG. Agentic workflows. Evaluation frameworks that grade output by code, by model, and by human, each catching a different class of mistake.
  • Async offload for long-running operations. The pattern that accepts a user request in under a hundred milliseconds and runs a five-minute job behind it without losing the thread. This one comes up in conversations more than any other backend topic right now.
  • Engineering enablement. Pairing on architecture. Code review with intent. Test-driven development. Clean statement-of-work hygiene. The unglamorous habits that compound across a team.

Below are three demos that show this in motion. Each runs in your browser.

RAG pipeline architecture diagram
RAG with evaluation
Indexing, retrieval, and three-lens evaluation
Demo 2
coming soon
Demo 3
coming soon

The async-offload reference (in progress)

Almost every team I have spoken with this year is in some stage of figuring out how to make their AI features feel snappy without dropping the long-running work on the floor.

I am writing this one up as a public reference. Code first. Posts second.

Contact

A question

What is the long-running operation in your stack right now that users wait on more than they should? I would like to hear how you are thinking about it.