Jorge P.

- Coordinate people across the world to build end to end systems.

- Design build and deploy multi agent systems to production, ensuring scalability and accuracy of results.

- Reduced by 95% time and cost spent on tasks by automating processes with Agents.

- Build data QA agents so data with MCP and google search grounding so the data team can investigate the company data and check veracity.

- Designed and deployed an AI-driven product matching system using Vertex AI and LangChain, integrating product name cleaning, Elasticsearch similarity retrieval, and AI-based decisioning.

- Built and deployed an AI agent using Google ADK and MCP capable of autonomously extracting structured data from web pages via Playwright MCP, replacing over 100 traditional web spiders.

- Researched and implemented a Kafka proof of concept, introducing real-time streaming into the company’s data ecosystem to support scalable and event-driven workflows.

- Modernized and optimized data pipelines using Airflow, Cloud Functions, Cloud Run, and Terraform, Big Query achieving up to 90% reduction in runtime and cost.

- Coordinate and lead data teams from several countries.

- Make data pipelines more efficient reducing their time and resources consumed in cloud. (AWS, Airflow)

- Deploy ML models into cloud (Terraform, AWS)

- Provide the analytics team the right data of the company so they can make proper analysis.

- Ensure data quality of the data since management team make their decisions based on it.