Systems & Enterprise Architect
About
Patent Examiner and Systems Architect specializing in cloud-native, distributed backend systems using Java 21, Spring Boot, Kafka, and Kubernetes. Combining rigorous academic grounding from Boston University (MSCS with a Security concentration) with enterprise-grade engineering experience across high-throughput telemetry pipelines, microservices modernization, and technical analysis.
Systems
Azure RAG Platform - Production AI System
Production RAG system using Azure OpenAI + AI Search. Secure document chat with citations. Built with TypeScript, Fastify, Bicep IaC, and Container Apps. Handles enterprise document workloads with sub-150ms inference.
Enterprise IoT Kafka Gateway - 10K+ RPS
Enterprise IoT telemetry gateway built with Spring Boot, Apache Kafka, Docker, Terraform. Processes real-time sensor data using Kafka producers/consumers, detects critical alerts at 10K+ RPS with 99.9% availability.
Spring AI Threat Detection Platform
Spring Boot microservice for real-time threat detection. Java 21, Spring AI, Kafka, Docker. Demonstrates production AI integration with event-driven architecture and sub-150ms threat scoring.
Redis Performance Proof - 85ms → 2ms
Redis @Cacheable implementation proving latency reduction. Spring Boot 2.6.6 + Java 17 + JPA + H2. Student GET endpoint: 85ms DB → 2ms Redis. Demonstrates JVM tuning + caching expertise.
Experience (Click to Expand)
- Architected cloud-native microservices and distributed platforms using Java 21, Spring Boot, AWS EKS, Kubernetes, and Apache Kafka
- Built Enterprise IoT Kafka Gateway for real-time telemetry ingestion and asynchronous processing
- Developed production AI capabilities using Spring AI and OpenAI RAG workflows, reducing database load by 60% while achieving sub-150ms API latency
- Optimized secure cloud platforms: caching improvements 85ms → 2ms, payment integrations, and production reliability enhancements
- Built event-driven microservices for legal intelligence and mortgage platforms using Java 21, Spring Boot, and Apache Kafka
- Designed scalable data ingestion pipelines supporting 10K+ RPS and asynchronous processing workflows
- Optimized high-volume backend data systems using PostgreSQL, Redis, and OpenSearch, achieving sub-150ms query performance
- Improved API performance by 75% (600ms → 150ms p99) through JVM tuning, Redis caching, and AWS optimizations while maintaining 99.9% availability
- Modernized legacy SOAP-based insurance systems into REST-based Spring Boot microservices deployed on GCP and AWS EKS
- Built document processing services using Java, Spring Boot, PostgreSQL, Redis, and Elasticsearch
- Reduced API p99 latency from ~600ms to ~150ms through SQL optimization, JVM tuning, Redis caching, Kubernetes, and Terraform
- Led national health system architecture development supporting 10M+ citizens across federal and regional offices; engineered RESTful services integrated with DHIS2 and distributed ETL pipelines for public health data; improved platform reliability by 90% and cut reporting time by 80% through SOA standardization.
- Designed distributed backend systems for national grant funding and technology transfer platforms supporting 15+ government agencies, automating workflows to boost operational efficiency by 70%.
- Developed a distributed fleet tracking platform using Java, Spring Framework, PostgreSQL, and Linux; built a TCP/IP telemetry gateway using Apache MINA and JMS/ActiveMQ to process 5,000+ concurrent events per hour.
Education
M.S. Computer Science — Boston University
B.S Economics and Management — Mekelle University