Alberto Rosas

AI & Agentic Systems Engineer with 12+ years in software engineering and 5+ years building production AI systems.

Key Projects

UCF AI Engine

Sole architect of the AI layer for a compliance SaaS

Hybrid retrieval (Qdrant + Neo4j) over 91K+ regulatory records, LangGraph agentic chat, CRAG hallucination verification. Docker/AWS.

SADIE

Production NL2SQL agentic platform

LangGraph + MCP tool-calling, MongoDB Atlas RAG pipeline, 93–97% query accuracy, Langfuse observability. FastAPI SSE.

TriageOps Framework

6-step AI adoption methodology

Discovery Sprints recovered 70+ hrs/month ($42K annually) for one operations team.

Technical Skills

LLMs & Models

GPT-4o, Claude, Gemini, Llama 3, Mistral, Qwen3, ModernBERT; fine-tuning (Unsloth, HuggingFace)

Agentic Systems

LangGraph, LangChain, MCP/tool-calling, multi-agent orchestration, multi-step reasoning, intent classification, memory systems

RAG & Retrieval

Qdrant, MongoDB Atlas, FAISS, Chroma, Neo4j, GraphRAG, hybrid retrieval (dense + sparse + graph), NL2SQL, context engineering

Evaluation & LLMOps

RAGAS, hallucination detection, latency benchmarking, Langfuse, Opik, Langsmith, MLflow, prompt versioning, CI/CD eval pipelines

Engineering

Python, TypeScript, PHP/Laravel, FastAPI, Docker, Kubernetes, AWS (Bedrock, SageMaker, EC2, S3, Lambda), CI/CD, Clean Architecture, microservices, event-driven systems

Experience

Unified Compliance

Senior AI Engineer (Contract)

2025 – 2026

Sole architect of the entire AI Engine for UCF's ControlSight compliance platform — 91K+ regulatory records.

• Built EEL pipeline: PostgreSQL → dense (ModernBERT) + sparse (BM25) embeddings → dual-load into Qdrant and Neo4j
• Designed hybrid retrieval: Qdrant vector+BM25 with Neo4j graph traversal, plus CRAG grading
• Built LangGraph agentic chat with intent classification, multi-turn context, query rewriting
• Modeled 8 entity types and 10+ relationships in Neo4j with Cypher queries and cross-store validation
• Evaluated using RAGAS (context recall/precision, faithfulness, answer relevancy)
• Directed company AI strategy, aligning AI capabilities with product, GTM, and data privacy

Storage360

AI Engineer (Contract)

2024 – 2025

Built SADIE — a production NL2SQL agentic platform for a property management SaaS.

• Built agentic workflow using LangGraph with MCP tool-calling and multi-step reasoning
• Implemented RAG pipeline with MongoDB Atlas vector search, Qwen3 embeddings
• Achieved 93–97% accuracy via RAGAS evaluation and CI/CD regression testing
• Built MCP server for secure read-only database access with schema caching
• Deployed via Docker Compose with Langfuse observability and FastAPI SSE streaming

IncFile (Bizee)

AI Engineer / Software Engineer / Technical Project Lead

2022 – Present

Leading AI strategy and platform architecture at a business formation SaaS.

• Designed multi-agent system for document processing, handling 1,000+ daily requests
• Built RAG pipeline with vector search; experimented with GraphRAG/KAG
• Implemented multi-layer memory systems for cross-session context retention
• Reduced manual data entry by 65% through intelligent form processing
• Led platform migration from legacy monolith to service-oriented stack with CI/CD
• Mentored 8 engineers on AI/ML development practices

Global Cybersec

Engineering Manager

2017 – 2021

Led engineering for a cybersecurity firm building security automation and incident response.

• Event-driven architecture processing millions of daily security events
• Integrated SIEM, IDS/IPS, firewalls, and SOAR — 60% reduction in incident response time
• Built 4 microservice applications, managed team of 5 engineers

Multiple Companies

Software Engineer

2014 – 2017

Full-stack roles across logistics, healthcare, and proptech.

• Built logistics platform (GT Transport) handling AP/AR, routing, payroll, HR
• Healthcare and proptech platforms with API design, testing, security

Education & Certifications

Universidad Politécnica de Baja California

Information Technology Engineering (2014–2016)

Laravel Certified Developer (2020) LangChain & LLMs Guide Gen AI Foundational Models Business Process Modeling with AI

Download Full Resume (PDF)

The Mushin Moment

2014. Mexico. Working accounts receivable. Only skill: fluent English from growing up in the US.

My boss asked if I knew someone who could build an internal system. I didn't know anyone. I didn't know anything about coding.

I said "I can do it."

Zero knowledge. Complete commitment. I taught myself, built it, delivered it. Years later I found the word: Mushin — 無心 — No-Mind. Freeing yourself from every obstacle by refusing to acknowledge them.