Aug 2025 – Present · 7 mos · Mumbai, Maharashtra, India · Hybrid

• As an AI Engineer, I successfully architected and implemented a Generative AI application on Databricks, utilizing advanced components such as vector stores, indexing, large language models (LLMs), and LangChain. My responsibilities included designing end-to-end pipelines for unstructured data ingestion, semantic search using vector embeddings, and seamless integration with LLMs for context-aware responses. I leveraged Databricks’ scalable infrastructure, ensuring efficient deployment and retrieval mechanisms while maintaining robust data governance. This project enabled smarter, context-driven query handling and significantly improved knowledge management and search experience within the organization.

Jan 2024 – Aug 2025 · 1 yr 7 mos · Mumbai, Maharashtra, India · Hybrid

• Designed and implemented scalable data architectures on Azure and Databricks, ensuring data integrity, security, and performance. Built and optimized ETL pipelines using Databricks workflow, integrating diverse data sources. Leveraged Databricks and Spark for efficient data processing and analytics. Automated infrastructure provisioning with Terraform, integrating it into CI/CD pipelines for seamless deployments. Optimized Spark jobs and SQL queries, improving performance and reducing data processing time by 60%. Successfully migrated on-prem data to Azure, enhancing scalability and cost efficiency. Additionally, worked on Generative AI (RAG) on Databricks.