Vetted Microservices Architecture Professionals

“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”

“DevOps/cloud infrastructure engineer focused on AWS automation: built GitHub Actions/Jenkins pipelines for containerized deployments with strong security controls and rollback, and implemented Terraform-based AWS provisioning with modular code and remote state/locking. Has led on-prem to AWS migration cutovers with structured risk/rollback planning and stabilization, but has not worked directly with IBM Power/AIX/LPARs or PowerHA/HACMP.”

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”

“Full-stack Java/Spring Boot + SPA (Angular/React) engineer who has delivered products end-to-end, including a financial management portal for SMBs and a high-traffic golf/hotel reservation platform. Notably migrated a manually deployed system to AWS (EC2/RDS/S3/CloudFront) with Jenkins CI/CD and has hands-on React performance optimization experience for LG webOS TV apps.”

“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”

“Built and owned end-to-end systems for the Department of Water Resources and NAHC, including a debt infrastructure management system and a TypeScript/React + .NET 6 CMS. Strong in shipping quickly with quality (CI/CD, automated testing), optimizing SQL Server performance for large datasets, and implementing microservices-style async processing with reliability patterns (retries/idempotency/monitoring). Also delivered widely adopted internal workflow automation and reporting using Power Automate and Power BI.”

“Robotics engineer who built an educational/research robotic arm end-to-end, including IK/FK math, simulation-based validation, and ROS2 Humble integration with multiple teleoperation inputs (DualSense and Leap Motion). Also optimized a resource-constrained ESP32-S3 wireless maze robot to stream real-time video and sensor data over WiFi using TCP/HTTP with RTOS-based concurrency and binary struct packing.”

“Full-stack engineer with experience delivering an end-to-end NIH application using Angular and scalable .NET Core microservices backed by MySQL. Has hands-on depth in complex approval/workflow implementations (RBAC + workflow engine) and performance tuning for million-record, data-driven systems, plus 5 years with Java/Spring Boot microservices and React.”

“Full-stack developer with ~2 years of Java experience who built an end-to-end workforce scheduling/rostering platform for a multi-branch coffee chain (200+ employees), including compliance and scheduling-rule enforcement. Also optimized a high-volume financial/accounting web app (transactions, payroll, invoices, HR) by improving backend logic and PostgreSQL performance with indexing, batching, and optimized joins.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”