Chaitanya Immanni

Supported the iBATIS team by developing LLM-powered chatbot solutions for internal tools. Used AWS Bedrock and embedding repositories for chunking and training models. Improved chatbot accuracy with custom prompt tuning and integrated analytics dashboards to monitor performance. Collaborated closely with product and UX teams for UI adjustments and workflow alignment.

Worked with Lowe’s AI/ML team to develop customer-focused recommendation models using Azure and Databricks. Built end-to-end data pipelines for training and inference workflows. Automated real-time predictions in retail systems and helped improve personalization for promotions and product search. Ensured deployment efficiency using MLflow and Azure Functions.

Implemented AI-powered chatbot support for T-Mobile by integrating price plans and CSM data into centralized pipelines. Automated data processing using AWS Lambda, Python, and Redshift. Contributed to the Sprint-to-T-Mobile CAMO migration by ensuring smooth data transition and enrichment. Supported model training workflows and collaborated across business and engineering teams.

Designed and built scalable data pipelines on AWS using Glue, Kafka, and Snowflake to process clinical and claim data in real-time. Collaborated with data scientists to provide high-quality, curated datasets for predictive analytics. Ensured HIPAA compliance and data integrity using validation checks and Airflow-managed workflows. Actively participated in Agile ceremonies, retrospectives, and production support.