Rails developer since 2006, now experimenting with AI integration and machine learning systems. Since 2022, I’ve been building intelligent applications using LLMs, FastAPI, and RAG architectures, combining my deep Ruby on Rails expertise with modern AI technologies. Currently developing an AI infrastructure platform that leverages both Rails backends and Python-based ML services for enterprise-scale deployments.
Rails Experience Since 2006 - Rails 1 through 8, from startups to enterprise scaleFull-Stack Development - RESTful APIs, GraphQL, ReactJS, NextJS, shadcn/uiPerformance & Scale - Database optimization, caching strategies, microservices architectureModern Rails Stack - PostgreSQL, Redis, Sidekiq, RSpec, Hotwire, Stimulus
AI & Machine Learning (2022-Present)
LLM Integration - Production deployments with GPT-4, Claude, and open-source modelsFastAPI Development - Building high-performance Python APIs for AI servicesRAG Systems - Implementing retrieval-augmented generation with vector databasesML Infrastructure - Model deployment, GPU optimization, streaming architectures
Led the architecture and implementation of a Ruby on Rails application redesign, resulting in improved performance and scalability for high-traffic loads
Designed and developed RESTful API endpoints, enabling seamless integration with third-party services and enhancing data flow across distributed systems
Implemented containerization for development and testing environments, improving deployment consistency and reliability
Established automated testing and continuous integration pipelines, significantly reducing defects and accelerating deployment cycles
Bachelor of Science in Electrical Engineering
University of Massachusetts, Amherst | 1987 - 1991
Field of Specialization: Telecommunications
Honors: Dean’s List