Juan Pablo Garcia Gonzalez
Solution Architect @ AWS Startups
Boston, Massachusetts, United States
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Juan Pablo Garcia Gonzalez is a Solution Architect with Amazon Web Services’ Startup team in Boston, Massachusetts. He works with high-potential startups to develop solutions on AWS Cloud. Previously, he spent over 20 years in software engineering, cloud architecture, and AI roles at leading technology companies such as Microsoft and Dell.
Juan Pablo regularly collaborates with the leadership and development teams of AWS top Startups, guiding them in co-innovation by leveraging AWS Cloud technologies. He is a frequent speaker at numerous industry conferences. As an engineer, Juan Pablo consistently contributes to technical communities, sharing his insights on technical topics such as AI and Cloud.
He holds an Electronics Engineering Degree from Mayor University, Information Technology management certificate from Pontificia Universidad Católica de Chile, a Master’s degree in Information Technology from Federico Santa Maria University and Building AI Product and Services certificate from MIT.
Area of Expertise
Topics
Multi AI Agent collaboration patterns
Discover how to build sophisticated AI systems that leverage multiple specialized agents working together to solve complex problems. This technical session explores four powerful multi-agent collaboration patterns—Agents as Tools, Swarms, Agent Graphs, and Workflows—and demonstrates how to implement them using the open-source Strands Agents SDK with Amazon Nova foundation models.
Building Production-Ready AI Agents with Amazon Bedrock AgentCore: From Concept to Deployment
Discover how to build and deploy AI agents leveraging comprehensive set of enterprise-grade services that help developers quickly and securely deploy and operate AI agents at scale using any framework and model, hosted on Amazon Bedrock or elsewhere.
Whether you're building a proof-of-concept or preparing for production, learn how to accelerate your time to market with just a few lines of code while maintaining enterprise-level security and scalability.
Introduction to Azure AI Agent Service
Azure AI Agent Service is a fully managed service designed to empower developers to securely build, deploy, and scale high-quality, extensible AI agents without needing to manage the underlying compute and storage resources.
This session is for software engineers who are looking to build the next generation of AI applications leveraging the power of AI agents.
We will review fundamentals such as what an agent is, why to use Azure AI Agent Service, and how to start building AI agent solutions with Azure AI Foundry.
Retrieval Augmented Generation (RAG) power by Azure AI Search
Retrieval Augmentation Generation (RAG) is a sophisticated system designed to augment the capabilities of a Large Language Model (LLM), such as ChatGPT. This enhancement is achieved by integrating an information retrieval system that provides grounding data. This integration allows for precise control over the grounding data utilized by the LLM when formulating responses.
In an enterprise setting, the RAG architecture facilitates the confinement of generative AI to specific enterprise content. This content can be derived from vectorized documents, images, and other data formats, contingent upon the availability of embedding models for such content.
In this session, we will delve into the concept of RAG and learn how to implement a RAG architecture. This architecture encompasses an Application User Experience (App UX) in the form of a web application for user interaction, an Application Server or Orchestrator serving as the integration and coordination layer, Azure AI Search functioning as the information retrieval system, and Azure OpenAI acting as the LLM for generative AI. This comprehensive learning experience promises to equip attendees with a robust understanding of RAG and its practical implementation.
Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
The future of AI is agentic. AI systems are evolving from having conversations to getting things done—this is where we expect much of AI’s value to shine. It’s the difference between generative AI recommending dinner options to agentic assistants that can autonomously place your order and arrange delivery.
This session is an introduction to understanding how Magnetic-One works, how it was built on top of the AutoGen framework, and how you can leverage the power of the AI Agent in your solutions.
Azure OpenAI patterns for software engineers
Azure OpenAI is a powerful service that enables developers to leverage the state-of-the-art language models from OpenAI to build intelligent applications. However, using Azure OpenAI effectively requires more than just calling the API. Developers need to understand the best practices and patterns for integrating Azure OpenAI into their solutions, as well as the limitations and challenges of working with natural language generation.
In this session, you will learn about the Azure OpenAI patterns, a set of guidelines and approaches to deliver common scenarios using Azure OpenAI. You will see how to apply these patterns to various use cases, such as. You will also learn how to optimize the precision and reliability of your Azure OpenAI applications, as well as how to handle errors, hallucinations, and user experience issues.
By the end of this session, you will have a solid understanding of how to use Azure OpenAI effectively and efficiently in your software engineering projects. You will also gain insights into the current and future capabilities of Azure OpenAI, as well as the ethical and social implications of natural language generation. Whether you are new to Azure OpenAI or already have some experience with it, this session will help you take your skills to the next level.
Enterprise Integration using Azure Serverless
Enterprise integration has been a challenge for long time, the enterprise organizations have deployed or built solution to solve their integration problems for their on-prem business application.
Now, in the new cloud age the enterprise integration challenge has mutated, solving in an easier way some traditional problems using cloud technologies like serverless but creating new challenges like Cloud to on-premise connectivity or end to end security.
On this session we will review some of the approach to use Microsoft Azure serverless services like Azure Functions and Logic Apps to solve enterprise integration problems, the experience to update some integration process based on Biztalk Server with Azure Logic Apps and some alternatives to connect process running on the cloud with applications and data on-premise. This session included process live demos integrating component in the cloud and on-premise.
Assistants API in Azure OpenAI
In this session, we will explore the API Assistants in Azure OpenAI Service. This new feature in Azure OpenAI Service, is now available in public preview. Assistants API represents a new cognitive architecture from OpenAI embedded in a product that makes it simple for developers to create high quality copilot-like experiences within their own applications. Previously, building custom AI assistants needed heavy lifting even for experienced developers. While the chat completions API is lightweight and powerful, it is inherently stateless, which means that developers had to manage conversation state and chat threads, tool integrations, retrieval documents and indexes, and execute code manually. Assistants API, as the stateful evolution of the chat completion API, provides a solution for these challenges.
Agentic AI: Unlocking the Power of Multi-Agent Systems
Dive into the dynamic world of Agentic AI with our expert-led session, “Unlocking the Power of Multi-Agent Systems.” In this comprehensive session, we’ll demystify the concept of agents within AutoGen—entities that can send and receive messages, generating replies using models, tools, human inputs, or a mixture of them. This multifaceted approach allows agents to mirror real-world and abstract entities, such as people and algorithms, streamlining complex workflows through agent collaboration.
Key Takeaways
Theoretical Foundations: Understand the core principles behind agents and their role in multi-agent systems.
Practical Demonstrations: Experience hands-on demos showcasing the practical implementation and collaboration of agents.
Extensibility and Composability: Learn how to extend simple agents with customizable components, creating modular workflows that are easy to maintain.
Real-World Applications: Discover how AutoGen is applied across various fields, from customer support and cybersecurity to finance and robotics.
Build your own Chat Copilot
In this interactive presentation designed for software engineers, you’ll learn how to construct your own intelligent Copilot chatbot. This session will delve into the utilization of Natural Language Processing and vector searching, among other capabilities. By harnessing the power of LLM-based AI, you can build the Copilot chatbot, enabling it to process and respond to information more effectively, including chat with your own data. To achieve this, we’re going to leverage the Semantic Kernel and its specific features that assist software engineers in quickly integrating AI capabilities into their solutions.
Boston Code Camp 39 Sessionize Event
Boston Code Camp 38 Sessionize Event
Boston Azure AI - Global AI Bootcamp 2025
Workshop of how to build your first multi-agent with Azure AI Agent Service and AutgoGen
Hands-on AI Workshop
Agent framework Workshop
> Overview of the Semantic Kernel Agent framework
> Creating your first agent
> Multiple agent orchestration
Hands-on AI Dev Workshop in BURLINGTON
Hello Boston Azure & North Boston Azure Community!
Join us at the Microsoft office in Burlington MA on Friday December 6, 2024, 9:00-4:00 where we are offering a free, full-day, hands-on AI-focused workshop focused on using Azure OpenAI and Semantic Kernel.
Boston Code Camp 37 Sessionize Event
Hands-on Azure AI Bootcamp
Hello Boston Azure Community!
Some final details have been added below. We are ready!
This is a full-day on Saturday Apr 20, 2024, 8:30-5:00, hands-on event on Azure with an AI-focus.
Labs will be offered in Python.
Content focus and associated labs will be on AI concepts and understanding them through hands-on experiences using Azure OpenAI features (and maybe some other adjacent features).
API Assistants in Azure OpenAI Service
In this session, we will explore the API Assistants in Azure OpenAI Service. This new feature in Azure OpenAI Service, is now available in public preview. Assistants API represents a new cognitive architecture from OpenAI embedded in a product that makes it simple for developers to create high quality copilot-like experiences within their own applications. Previously, building custom AI assistants needed heavy lifting even for experienced developers. While the chat completions API is lightweight and powerful, it is inherently stateless, which means that developers had to manage conversation state and chat threads, tool integrations, retrieval documents and indexes, and execute code manually. Assistants API, as the stateful evolution of the chat completion API, provides a solution for these challenges.
Boston Code Camp 36 Sessionize Event
Boston Code Camp 35 Sessionize Event
Boston Area Global Azure Bootcamp Sessionize Event
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