Backend and distributed systems engineer
Fourteen years of backend engineering, most of it in Java on AWS. Nine of those years were at Amazon and three and a half at PayPal, where I owned technical reconciliation for the in-house card processing platform. I left PayPal in March 2026 and now build and run nextbookinorder.com, a reading-order catalogue for book series. Its LLM content pipeline runs behind deterministic quality gates.
Open to Staff and Lead backend roles. Remote in the US, or hybrid in Austin, Texas.
In four numbers
Selected work
Two are from employers and use only the figures on my resume. Two are my own, so the numbers go deeper.
Technical reconciliation for Lynx, PayPal's in-house card processing platform. An hourly job on the happy path, and an event-driven rerun for any hour that receives late records.
I owned the telemetry pipeline and client library for the delivery associate app while its fleet grew from 70K+ associates to about 1M registered. I re-architected both, and moved live traffic with old and new running in parallel.
A reading-order catalogue for book series, more than 68,000 pages, that I built and run end to end. Its LLM pipeline writes nothing when a page has no usable source, and my rule is that each class of bug that ships gets a check in the deploy gate.
I direct AI coding agents. I give them a written bar and a separate reviewer, and I'm trying out a local model for the mechanical work. Most of my code is written this way.
Experience
2026 to now
A reading-order catalogue for book series, more than 68,000 pages, built and run end to end. Its LLM content pipeline runs behind deterministic quality gates.
2022 to 2026
Owned technical reconciliation for Lynx, the in-house card processing platform. Nominated for promotion to Staff Software Engineer in Sep 2025.
2013 to 2022
Nine years across five roles: Fulfillment Technology, Prime Video Live Events, Last Mile, Supply Chain Optimization, and the Amazon.com seller and B2B pages.
2010 to 2011
Cut a retail portal page load from 28 s to 2.5 s by redesigning its SQL and data flow.
How I work
At PayPal I had four upstream teams and no reporting authority over any of them. PoCs and written trade-offs, taken through architecture and design reviews, got the data contracts agreed. Read the PayPal case study
At Amazon the new telemetry pipeline took live traffic while the old one kept running. The dashboards operations depended on kept working through the move. Read the Amazon case study
On my own product the deploy gate grew from 29 check functions to 63 in two months. My rule is that a bug that ships once gets a new check in the same session. Read the nextbookinorder case study
In one run, 5 of 6 AI verifier agents reported a clean result without running the check they were assigned. I found out by reading which check each one said it had run. Read the AI agents case study
Remote in the US, or hybrid in Austin, Texas. LinkedIn is the fastest way to reach me.