Building at the intersection of data, AI, and enterprise platforms — turning complex problems into elegant, scalable solutions.
// about me
I'm a Distinguished Technical Architect on Data and AI at Salesforce, specializing in helping enterprise customers architect and deliver data strategies that power AI-driven outcomes at scale.
With dual master's degrees in Data Science (Northwestern University) and Data Engineering (WGU), I bring both theoretical depth and hands-on engineering skills to every engagement — from pipeline design and feature engineering to ML model deployment and governance.
Before tech, I served in the U.S. Military, which shaped how I approach every problem: with discipline, systems thinking, and a bias for getting things done under pressure.
I'm fluent in English and Spanish, passionate about data governance and the responsible use of AI, and always exploring the next frontier — currently LLMs, Agent-to-Agent (A2A) protocols, and MCP.
// tech stack
// featured work
The headless home page for the relationship banker. Claude 4.5 Sonnet orchestrates Salesforce CRM, Data Cloud, and Tableau Next MCP servers behind a no-navigation, conversation-first UI. Built for the DAX "So You Think You Can AI?" Innovation Contest.
Heroku-hosted MCP server exposing 43 Salesforce Data 360 / Data Cloud tools across 16 families. Dual transport (SSE + stdio), dual auth (OAuth + SF CLI), and write-operation guardrails — read-only filtering, destructive-action confirms, and structured audit logs.
Benchmark tool that compares token cost between Salesforce native (sf CLI) and Salesforce-hosted MCP servers. FastAPI backend with OAuth 2.1 + PKCE, vanilla-JS frontend, free-format prompts, and PDF export.
Synthetic financial transaction simulator with overdraft prevention, balance tracking, and deep Salesforce Data Cloud / Snowflake integration.
Quick setup and demo of implementing MCP (Model Context Protocol) for Salesforce Data 360 (Data Cloud), enabling LLM-native data access patterns.
Collection of Salesforce-related code covering CRM Analytics, Einstein Discovery, BYOM (Bring Your Own Model), and TensorFlow integrations.
Salesforce DX project containing LWCs, Apex, flows, and demo metadata for Jose's Demo Org. The companion org behind every live walkthrough and prototype.
Reference guide for building LLM applications with LangChain — prompt templates, LCEL chains, agents, tools, and end-to-end RAG pipelines.
Reference guide for the OpenAI API, Hugging Face Transformers, embeddings, semantic search, ChromaDB, and Pinecone vector databases.
Personal reference guide covering core DSA concepts — Big O, linked lists, stacks, queues, trees, graphs, sorting, dynamic programming, heaps, and more.
Reference guide for core Python concepts — object-oriented programming, error handling, and testing with pytest and unittest.
More on GitHub →
// thought leadership
An exploration of how data clean rooms enable privacy-preserving collaboration between organizations without exposing raw data.
Read on LinkedIn →A practical introduction to data governance frameworks, ownership, lineage, and why it's the foundation of every successful data strategy.
Read on LinkedIn →A breakdown of ETL, ELT, and modern data integration patterns — when to use each and how cloud data warehouses changed the equation.
Read on LinkedIn →What vector databases are, how they differ from traditional stores, and why they're essential infrastructure for LLM and RAG applications.
Read on LinkedIn →More at analyticsmadesimple.com →
// credentials