AI Engineer · Production AI Platforms · Multi-Agent Systems
RAG Architectures · Agentic Orchestration · Enterprise AI
AI Engineer · Production AI Platforms · Multi-Agent Systems
RAG Architectures · Agentic Orchestration · Enterprise AI
With 13+ years in production systems engineering and a deep focus on applied AI, I build the platforms that turn AI capabilities into enterprise reality. Multi-agent orchestration systems, RAG architectures for enterprise knowledge bases, and intelligent assistants that solve complex business problems at scale.
My background in enterprise environments—where reliability, security, and compliance are non-negotiable—shapes everything I build. I've led cross-functional investigations across engineering and product teams, run stakeholder syncs with senior executives, and translated complex technical work into clear business outcomes. I bring that same production mindset to AI: well-tested code, robust API integrations with OpenAI and Anthropic, and systems architected for real-world deployment.
Production LLM infrastructure with RAG pipelines, GPU-accelerated inference, and seamless integration with OpenAI and Anthropic APIs
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Building Model Context Protocol servers for seamless AI integration with Claude Desktop and custom applications
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End-to-end Python applications, intelligent data processing pipelines, and production-ready API development
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Intelligent assistants, internal automation tools, and custom AI solutions designed to solve complex enterprise challenges and accelerate workflows
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Multi-agent orchestration for development workflows using Claude Code, Cursor, and GitHub Copilot—autonomous agents that write, review, and ship production code
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Transforming the software development lifecycle with AI agents at every stage—from code generation to CI/CD to deployment—accelerating delivery while humans lead and validate
Learn more →Python • OpenAI API • Anthropic API • CUDA • LM Studio
Designed and deployed production AI infrastructure supporting both local and cloud LLM providers. Custom Python bridges connect LM Studio, OpenAI, and Anthropic APIs with MCP servers, enabling advanced tool integration and enterprise-grade AI capabilities.
View case study →Python • MCP • Claude Desktop
Production-ready Model Context Protocol servers for database management, analytics, and project tooling. Enables intelligent AI assistants to interact directly with enterprise systems, databases, and files through a secure, standardized protocol.
View case study →Python • NLP • Multilingual AI
Generates content in multiple languages. Local LLMs via LM Studio power personalized, context-aware content creation—processing thousands of profiles without per-request API costs.
View case study →Python • ETL • Data Analytics
Developed ETL pipelines to process UAD datasets for context aware market analysis. Transforms raw property data into actionable investment intelligence with configurable analysis workflows coming soon.
View case study →Python • C/C++ • RAG • LangChain • AST
RAG-powered code translation converting legacy C codebases to idiomatic Python. Dependency-aware context retrieval ensures semantic accuracy while local LLMs via LM Studio eliminate translation costs at scale.
View case study →Python • Vision-Language Models • Local-First
A local-first semantic image search system using vision-language models. Automatically describes, tags, and indexes images for natural language querying—no cloud dependencies required.
View case study →AI Engineer & Solutions Architect
I spent seven years as a senior systems engineer at FreeWheel, a Comcast company, building and supporting enterprise-scale ad-tech infrastructure. I led cross-functional investigations coordinating across engineering, product, and client teams. I automated reporting workflows with Python and pandas, built diagnostic tooling that became go-to resources for the broader engineering team, and ran biweekly stakeholder syncs translating technical complexity into clear business language for senior leadership.
Now I apply that enterprise production mindset to AI full-time. I design multi-agent orchestration platforms, build RAG pipelines for enterprise knowledge bases, and develop intelligent assistants that solve real business problems. I work with LangChain, LangGraph, OpenAI, and Anthropic APIs, and I ship with the rigor that comes from 13 years in environments where systems have to work at scale. I believe great technology is measured not by its sophistication, but by how effectively it solves actual problems.
Building multi-agent AI systems? Need production-grade intelligent assistants? Looking to deploy AI at enterprise scale? Let's talk.