Software engineer building at the intersection of backend, data, and applied AI. Four years turning business problems into systems that ship, scale, and stay maintainable instead of rotting into tech debt.
Comfortable across the stack —from data model to frontend— but my current focus is RAG, MCP, and MLOps architectures over corporate data. I care that the AI systems I design are operable, observable, and debuggable in real production.
I give talks on AI and data science at universities —Tec de Monterrey, UPVM Tultitlán and TESCo— to audiences of ~200 people, closing the loop between academic theory and what actually happens once a system meets production.