I started where most engineers do — building what clients asked for, shipping it, moving on. But over four years across production systems, something shifted. I began designing for the why, not just the how.
In that time I've shipped REST APIs handling 50,000+ daily requests, cut response times by ~40% through schema and query work, migrated production infrastructure between cloud providers without downtime, and integrated everything from POS systems and Stripe to Claude and GPT-4o into live applications.
More recently, as the sole engineer at Tamarind Collection, I've owned a customer-facing platform end-to-end — and built an internal admin tool from scratch that replaced manual KPI workflows for senior stakeholders. The kind of work where you're translating frustration into something that actually runs.
My MSc at the University of East London pushed me into applied AI — an end-to-end Alzheimer's detection pipeline (87% accuracy), 10M+ row Spark workloads, and the question underneath it all: what does it take to move intelligent systems from a notebook into production?
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