22-25 April 2026

Carlos Contreras

Since 2018, Carlos has been working as a Big Data & Generative AI Architect at Amazon Web Services, in London. Before Amazon, Carlos worked in the UK for a startup as Lead of Data; and for Online Banking (WorldPay) as a Data Warehouse architect. Before moving to England, Carlos worked for 10 years in Spain as a Data consultant for companies like General Electric and Inditex (Zara, Massimo Dutti, Bershka, Oysho) at their global headquarters in La Coruña. Before living in Spain, Carlos worked in Mexico City and the United States, for the Mexican Stock Exchange and General Electric in New York.

Carlos Contreras's Sessions

AI Agent Orchestration in Action: SQL Server Meets AI-Powered Sports AnalysisSQLBits 2026

Learn to architect and orchestrate multiple specialized AI agents, using AWS Bedrock AgentCore and open-source Strands Agents framework. Through hands-on examples, build a multi-agent system that intelligently queries SQL Server football databases for sports strategy analysis. Explore agent coordination patterns, workflow orchestration, and practical implementation techniques for complex analytical tasks.

Voice-Driven SQL Server Supply Chain Intelligence: Build Speech-to-Speech AI Agents with AWS & MCPSQLBits 2026

Build voice-enabled AI agents using Amazon Nova Sonic and MCP servers to query SQL Server logistics databases. Learn to create speech-to-speech systems that track trucks, inventory, and warehouse operations through natural conversation. Explore practical patterns for integrating voice AI with SQL Server supply chain data.

Natural Language to TSQL: Mininimizing LLM Hallucinations in SQL Server database queries on AWSSQLBits 2025

Explore techniques to transform natural language into SQL Server queries, using Generative AI on AWS. Learn strategies to minimize LLM hallucinations and improve query accuracy for database interactions, with a low-code approach.

How Formula 1 automated their SQL Server Database Ops & Health Checks on AWS, using AI AgentsSQLBits 2025

In this session, we show you how F1 created an AI-powered purpose-built root cause analysis (RCA) assistant, to empower users such as operations engineers, software developers, and network engineers to troubleshoot issues, narrow down on the root cause, and significantly reduce the manual intervention required to fix recurrent issues during and after live events.