About Me
Backend engineer with 6+ years of experience building distributed systems and cloud-native microservices at scale. My foundation is in high-traffic production architecture — payment systems serving millions of users, compliance-grade APIs, and zero-downtime CI/CD pipelines. Over the past year I've deliberately shifted toward AI-native backend engineering: building platforms where LLM capabilities are infrastructure-layer components, not UI features. I treat AI tooling as an engineering multiplier and I'm most energized building the serving layers that enable AI-driven user experiences to work reliably at scale.
Skills
Technologies and concepts I work with
Concepts & Patterns
Other
Experience
Java Developer
Building and maintaining distributed FTPC server infrastructure for Manufacturing Execution Systems (MES) across regulated global production sites — applying production-grade reliability and compliance discipline to critical manufacturing data pipelines.
Software Engineer
Architected and launched a large-scale installments payment platform in the CA marketplace, serving 5M+ customers and generating over $500M in revenue within six months — owned end-to-end from design through production monitoring.
- Designed horizontally scalable, idempotent microservices in Java and Spring Boot deployed via Docker, Kubernetes, and Helm on AWS — achieving 30% faster transaction processing than the US baseline through targeted service-level optimization.
- Built a compliance-grade data-deletion API reducing response times by 40% — balancing throughput, correctness, and auditability under strict regulatory constraints.
- Optimized DynamoDB access patterns and query models for the SettleForLess project, reducing response times by 40% through schema redesign and read amplification reduction.
- Owned CI/CD pipelines end-to-end: phased rollouts, peak traffic handling, and observability across a cloud-native environment — zero scheduled downtime across the deployment lifecycle.
Software Engineer
Designed a Spring-based backend API layer enabling real-time communication between ML inference services and airport security hardware — early hands-on exposure to the challenges of productionizing model-serving workflows.
- Improved CI/CD pipeline reliability with Jenkins, reducing release cycles for ML-integrated features.
Software Engineer
Built backend services for Azure-hosted automated payment workflows, reducing production defects by 15% through structured testing frameworks and Swagger-integrated API validation.
- Developed an internal chatbot using Microsoft Bot Framework — early exposure to conversational system design that now informs how I think about LLM-integrated backend architecture.