AI Engineer building RAG systems, multi-agent workflows, and data pipelines — usually pointed at finding, generating, or qualifying leads.

Python · C#/.NET · Azure · OpenAI · Semantic Kernel · AutoGen · Streamlit · SQL

I ship things people can actually run — including ai-blog-app, an open-source Python library for multi-agent content generation, published on PyPI.

📊 Turning public data into qualified leads Structural Risk Index — extracts code violations from municipal PDFs across three cities and scores 1,089 properties with a weighted risk model, surfaced in an interactive dashboard. It started while I was helping an investor find distressed properties worth approaching. Built at LandingAI Financial Hack NYC 2025.

🤖 Multi-agent content generation ai-blog-app — a writer, a critic, and three specialized reviewers (SEO, content marketing, clarity and ethics) collaborate to produce and refine content autonomously. Built on Microsoft AutoGen; supports OpenAI, Gemini, Claude, and local models via Ollama. Open-sourced under MIT and published to PyPI as a Python library — pip install ai-blog-app.

🔍 RAG & document intelligence RAG Document Assistant — answers multilingual questions grounded in a private collection of government PDFs, using .NET 8, Semantic Kernel, Azure OpenAI, Qdrant, and Docker. I built it because a relative was navigating a Canadian humanitarian program buried in conflicting official information.

Industrial and software engineer — though I started programming out of impatience. I was selling leads and running landing pages, and every small change meant calling a developer and waiting. Learning to do it myself turned out to be faster.

Before returning to engineering full-time in 2022, I worked in lead generation and marketing: PPC, email automation, and teaching real estate professionals to automate their pipelines with tools like Zapier.

That's why my projects start from a real business problem rather than a framework I wanted to try, and why they keep landing near acquisition — sourcing prospects from data nobody has cleaned, generating content that ranks, routing leads to the right person. Industrial engineering is process optimization, and that turns out to be most of what building with AI actually is.

Hackathons: LandingAI Financial Hack NYC 2025 · Microsoft .NET Hack Together Certified: Google Data Analytics

Remote AI engineering roles — full-time or contract.

Independent projects. RAG and document AI, data pipelines from extraction through analysis, multi-agent automation, and custom AI applications. I'm most useful where AI meets growth: data trapped in documents or disconnected systems that should be telling you who to talk to next.

💼 LinkedIn · 🌐 Portfolio · 📦 PyPI

Hablo español. 💃