Jorge Vilaseco

Architected an intelligent code generation platform processing XML specifications into multi-language codebases, applicable to medical device configuration and energy system automation. Led XML schema definition and template architecture design, collaborating with stakeholders to establish robust specifications enabling flexible and consistent code generation workflows.

Enhanced system architecture with a robust authorization layer ensuring GDPR/HIPAA-compliant data security for sensitive financial data. Strategically assessed database design, advocating for the migration from DynamoDB to RDS to leverage built-in transactions, fostering a more structured and efficient development process.

Achieved 80% performance improvement in a PDF viewer through virtual scrolling, enabling efficient handling of large files without loading or scrolling lag. Implemented advanced data annotation workflows with drag-and-select functionality for AI training data preparation, enhancing the user experience.

Redesigned monolithic architecture into microservices, achieving 20% performance gain and 70% memory reduction. Increased the resilience and scalability of the service by moving it from an EC2 instance to an ECS service that provides automated management of the EC2 instance while keeping the infrastructure simple.

Pioneered real-time monitoring SaaS using NestJS, AWS ECS, Angular, and WebSockets—a framework applicable to patient monitoring and energy grid observability. Created a CI/CD pipeline updating AWS ECR and ECS, streamlining deployment processes.

Led the implementation of the network microservice of an event-driven application to automate infrastructure creation, introducing Typescript with NodeJS to the team to increase code maintainability. Trained colleagues in charge of other microservices in the use of Javascript and Typescript.

Led a mixed team of experienced and fresh graduates in a Big Data visualization app for factory data tracking. Fixed rendering and lag issues in NGX Charts for large datasets by reverse engineering an OpenSource library and identifying and fixing rendering redundancies.

Activities and societies: Practical application of multi-agent systems for industrial automation.

Currently mastering modern AI frameworks such as CrewAI, LangGraph, and AutoGen. Focused on the practical application of multi-agent systems for complex industrial automation, including the latest Model Context Protocol (MCP).

Focused on software development principles and practices. Gained foundational knowledge in programming, data structures, and algorithms relevant to modern software engineering.