Led the migration of pipelines using Retrieval-Augmented Generation (RAG) approaches and model fine-tuning, enhancing analytical processes and ensuring greater efficiency and performance in critical systems. Transformed R pipelines to PySpark, integrating advanced data processing strategies.

Developed full-stack solutions including data automation and web scraping for capturing and processing agricultural sector information. Created mobile applications using Expo, React Native, and TypeScript, as well as front-end websites with Next.js and back-end with PostgreSQL, NestJS, and Prisma. Integrated and created scalable APIs.

Developed mobile applications and integrated APIs with machine learning models, optimizing processes and improving efficiency in the agricultural sector. Created and optimized algorithms in Node.js, ensuring high performance and scalability in developed solutions.