nicks

By building a multi-service architecture with a Go ingestion API, RabbitMQ message queue, Python AI worker (Ollama), PostgreSQL, and Redis, created a system that automatically classifies log severity, identifies root causes, and suggests actionable fixes all orchestrated via Docker Compose with 7 coordinated services. • Engineered a real-time observability dashboard using Next.js and React with live polling that detects new AI diagnostics and updates the UI without manual refresh, providing charts, analytics, and detailed log views. • By applying AI-assisted development practices including spec-driven prompting, structured code review, and architecture planning, Accelerated feature delivery while maintaining code quality, scalability, and Clean Architecture standards.

Processing 3M+ heterogeneous records in under 22 hours, built a batch-processing data pipeline using Golang with GORM, React, WebSocket, and Redis that transformed 1M+ uncategorized files (.csv, .docx, .txt) into structured, actionable health insights for hospital managers. • Delivered a real-time analytics dashboard built in React that transformed raw healthcare records into visual insights including trend analysis, service distribution, and risk indicators empowering health managers to identify operational gaps and prioritize resources.