I design intelligent systems at the intersection of AI, blockchain, and quantum technologies. My work is rooted in systems thinking and driven by cross-domain innovation—transforming complex research into scalable, real-world solutions.
class Ricardo:
"""Full-Stack AI Engineer | Multi-Agent Systems | Knowledge Graphs | Quantum Computing"""
stack = {
"AI": ["LangGraph Multi-Agent", "Graph RAG", "Vector Search", "AWS Bedrock"],
"Data": ["Neo4j + GDS", "MongoDB", "PostgreSQL", "Graph ML"],
"Languages": ["Python", "Rust", "Go", "TypeScript", "Solidity"],
"Blockchain": ["Hyperledger Besu", "Smart Contracts", "Web3", "EVM"],
"Infra": ["AWS", "Kubernetes", "Docker", "CUDA/ROCm"],
"Quantum": ["IBM Qiskit Certified", "VQE/QAOA", "127-qubit"]
}
certifications = ["Deloitte AI", "IBM Quantum", "NVIDIA Supercomputer"]- Semantic Code Intelligence - Building tools for navigating AI-generated codebases through concept-based search
- Supervisor Multi-agent Systems - Coordinating specialized AI agents with LangGraph + Neo4j/MongoDB/ChromaDB backends
- Self-hosted LLM Infrastructure - Running private, scalable AI systems on local dedicated hardware
- semantic-code - MCP server for semantic code search using AST-aware chunking and vector embeddings
- supervisor-multi-agent-system - Multi-agent architecture with central supervisor and specialized workers
- bmad-architecture-agent - Expert architect toolkit for the BMAD-METHOD framework
- Navigate by Meaning - How semantic search cuts AI code assistant token usage by 67%
- Thinking In Human - Reclaiming comprehension in an age of AI-generated code
- Building Multi-Agent Systems - A supervisor architecture deep dive with LangGraph
