Designed and implemented a RAG and Machine Learning process that gathered and processed information from other electric utilities through APIs and web scraping, making the data available for AI-powered search and analysis. Designed and maintained scalable data pipelines to process data from multiple sources across the energy business.

Led and participated in all phases of the software development lifecycle for multiple projects for Japan’s largest telecommunications operator, including requirements analysis, system design, development, and deployment with neural networks

Designed and developed AI-powered solutions using LLMs, RAG, LangChain, and vector databases for companies across domains such as news, video games, and image-based content. Built end-to-end RAG pipelines and REST APIs, covering data ingestion, embeddings, semantic search, retrieval, and LLM integration to deliver domain-specific AI solutions.

Led part of a Google-partnered project, developing AI solutions on Google Cloud Platform for document processing, data extraction, and classification using Document AI and Cloud Vision. Developed AI agents leveraging Retrieval-Augmented Generation (RAG) techniques to retrieve and synthesize information about exports and products from multiple data sources.

Designed and implemented scalable ETL/ELT pipelines to process and manage large-scale geolocation data. Integrated AI/ML workflows to predict venue performance across the U.S., leveraging location and movement data along with demographic information.

Developed an architecture of microservices for an integration and BPA system in AWS. Led the development of an architecture for a web scraping bot to get, post and update data in different websites related to the property management business.

Created different data pipelines and serverless solutions for Fintech and financial companies. Developed high-performance web services and APIs to deliver real-time information efficiently. Managed cloud resources to ensure operational efficiency and optimal system performance.

Created machine learning models to get predictions on participation in online courses. Cleaned and preprocessed raw data to handle missing values, and inconsistencies, ensuring data quality and integrity for downstream analysis and modeling.