Carlos Urteaga

Ph.D. student and Data Scientist at Globant focused on the operational maturity of AI Agents.

He designs and deploys agentic AI systems in production environments, bridging research, engineering, and governance.

With over nine years of experience across Financial, Educational, Retail, and Telecommunications sectors, he has built scalable AI workflows, RAG systems, and LLM-powered agents with strong emphasis on evaluation, monitoring, and reliability in cloud environments.

His research introduces practical standards for agent governance, including Agent Cards, Agent Contracts, Agent Types, and Agent Ledgers—a framework for documenting, validating, and operating AI agents with accountability and traceability.

His broader interests include AgentOps, LLMOps, RAG evaluation, and responsible autonomy for multi-agent systems.

He is open to research collaborations and internships related to operational AI, agentic architectures, and AI governance.