WORK
Senior Full Stack Engineer with 14+ years building distributed systems, cloud and data platforms, and full-stack products — increasingly using AI to improve how engineering teams design, deliver, and operate software.
I gravitate toward complex, consequential problems: systems with large audiences, high-throughput traffic, demanding latency targets, and data models that have to keep working as their scale changes. My role often stretches from architecture and backend services through data, cloud infrastructure, delivery pipelines, testing, and the user experience.
The direction of my work is toward Staff- and Principal-caliber scope: taking ownership of ambiguous problems, connecting decisions across teams, and carrying solutions from an early idea into reliable production systems. I am also drawn to forward-deployed-style engineering — staying close to real users and operational constraints, then turning what I learn into durable platform capabilities.
Senior Full Stack Engineer · 2025 — Present · Westlake, Texas
Working on enterprise personalization and data platforms with Java, Spring Boot, AWS, event streaming, distributed data technologies, and modern delivery platforms. My focus includes scaling high-throughput services, reducing latency and data footprint, evolving data models, and improving engineering productivity with AI-assisted development and stronger automated testing.
Wells Fargo · Synechron · Virtusa · Infosys · TCS
Built and supported financial technology systems across enterprise application engineering, distributed caching, backend services, data-intensive platforms, cloud adoption, and full-stack delivery. Those roles shaped how I approach performance, reliability, migration risk, and long-lived systems.
I built an early proof of concept to explore how a matching engine can discover multi-party exchange circles from offers, needs and constraints. The fictional Maple Commons community lets me test explainable matches, participation preferences and human approval before considering real-world exchanges.
I am also exploring how the matching network could become an agent-callable capability, with the website as one interface. This is a personal experiment, not a production service.
Read the BarterSystem build update and see screenshots → · Explore the repository ↗
I like to understand the whole path: the problem a user is trying to solve, the data moving through the system, the failure modes, deployment and observability, and the performance characteristics that emerge at scale. The best engineering work, to me, combines technical depth with ownership, clear judgment, and close collaboration.