R
Ramya Banothu
About
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Plainfield, Indiana, United States
Résumé
Jobs
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Generative AI EngineerathenahealthSep 2024 - Current (2 years)As a Generative AI Engineer, I specialized in GenAI Pipeline Architecture and LLM Deployment, where I architected and deployed three end-to-end RAG pipelines for clinical Q&A, prior authorization automation, and patient note summarization using LangChain, Pinecone, and GPT-4/LLaMA 2, effectively reducing clinician documentation time by approximately 35%. I built a HIPAA-compliant LLM-powered clinical documentation assistant that processes over 500,000 patient notes monthly, integrating PII de-identification techniques (Azure Presidio + custom NER) before LLM inference to ensure zero PHI exposure. My work included fine-tuning domain-specific models (LLaMA 2 7B, Mistral 7B) using QLORA and PEFT on more than 2 million de-identified clinical re- Data Analyst / Data EngineerDeloitteJul 2021 - Jul 2023 (2 years 1 month)As a Data Analyst / Data Engineer, I specialized in Data Engineering and ETL Pipeline Development, where I designed and delivered over 12 production ETL pipelines using Informatica PowerCenter to ingest structured (Oracle, SQL Server, Teradata) and semi-structured (JSON, XML, CSV) data into enterprise data warehouses, processing more than 50 million records daily. I built automated SQL workflows, including stored procedures, views, triggers, and window functions on MS SQL Server, Teradata, Oracle, and BigQuery, which reduced manual reporting efforts by 60% through scheduled batch execution. My role involved developing complex transformation logic using Informatica components for multi-source financial data consolidation, serving over five b
Education
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- OOracle certified-Generative AlJul 2025 - Aug 2025 (2 months)
- Master's of computer scienceUniversity of North TexasMay 2025Denton, TX
Projects (professional or personal)
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- MMulti-Agent LangGraph WorkflowSep 2025 - Dec 2025 (4 months)As a Multi-Agent LangGraph Workflow specialist, I focused on automating document classification and routing processes using AutoGen, LangGraph, and CrewAl, significantly enhancing operational efficiency. My role involved leveraging data analysis and data science techniques to optimize workflows, ensuring accurate and timely document handling. Additionally, I utilized Python and Streamlit to develop user-friendly interfaces for monitoring and managing the automated processes. While Neo4j was not a primary focus, my understanding of graph databases contributed to the effective implementation of LangGraph in our workflows. Furthermore, I maintained a commitment to software maintenance and technical documentation, ensuring that all systems were
- LLLM Fine-tuning PipelineJan 2025 - Apr 2026 (1 year 4 months)As an LLM Fine-tuning Pipeline specialist, I focused on the QLORA fine-tuning of the LLAMA 2 7B model specifically tailored for healthcare text, utilizing Parameter-Efficient Fine-Tuning (PEFT) techniques. I meticulously tracked the fine-tuning process with MLflow, ensuring robust monitoring and reproducibility of experiments. The model was served via Hugging Face Inference Endpoints, facilitating seamless integration into applications. Additionally, I leveraged my knowledge of Neo4j to explore relationships within healthcare data, enhancing the model's contextual understanding. While Streamlit and R were not directly utilized in this role, my experience in data analysis and data science allowed me to effectively interpret results and docum
- CClinical RAG Q&A SystemFeb 2024 - May 2024 (4 months)End-to-end RAG pipeline (LangChain + Pinecone + GPT-4) for HIPAA-compliant clinical Q&A; deployed via FastAPI on AWS SageMaker.