Gaman y
Ai Ml Engineer @Optum
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WORK HISTORY
Ai Ml Engineer @Optum
US
At Optum, a subsidiary of UnitedHealth Group and a key player in healthcare technology and services, I\'m contributing to AI-driven solutions within the Optum AI Marketplace, Clinical Language Intelligence (CLI), and Revenue Cycle Management (RCM) systems. These initiatives center around deploying AI to overhaul administrative workflows, enhance clinical documentation quality, and deliver compliant, intelligent APIs for healthcare providers and payers. Functional role details:• Designed and deployed AI/ML models for claims automation, fraud detection, and patient risk scoring.• Built NLP pipelines with LangChain, Hugging Face, spaCy to extract ICD/CPT codes and medical insights.• Implemented RAG workflows using FAISS/ChromaDB to improve accuracy and reduce model hallucinations.• Developed backend APIs (FastAPI, Flask) and deployed on AWS Lambda and Azure Functions for scalable, low- latency access.• Automated ETL and data pipelines with Azure Data Factory, Spark, and Airflow for large-scale healthcare datasets.• Enhanced Revenue Cycle Management (RCM) and Clinical Language Intelligence (CLI) platforms, improving coding speed and accuracy.• Designed real-time dashboards in Power BI and Tableau to monitor model KPIs, claims performance, and patient engagement.• Ensured compliance with HIPAA, PCI DSS, and RBAC standards, embedding validation and monitoring into ML workflows.• Optimized cloud-native deployments with Docker, Kubernetes, and CI/CD pipelines for reliable production rollout.• Mentored cross-functional teams on Generative AI, prompt engineering, and responsible AI adoption across healthcare applications
EDUCATION
VNR Vignanajyothi Institute of Engineering & Technology
Bachelor of Technology - BTech
University of North Texas
Master's degree
ABOUT GAMAN Y
AI/ML Engineer with 4+ years of experience delivering Generative AI, NLP, and ML solutions across finance, retail, and food tech. Specialized in Conversational AI, Multi-Agent Systems, and RAG pipelines with expertise in LangChain, LangGraph, and OpenAI APIs. Skilled in designing scalable backend APIs (FastAPI, Flask, Django) deployed on AWS, Azure, and Kubernetes, and in building deep learning/NLP models (CNNs, RNNs, LSTMs) for sentiment analysis, fraud detection, and personalization that drive measurable business impact. Strong background in the full data science lifecycle, cloud ML deployment (SageMaker, MLflow, Azure Data Factory), and BI tools (Tableau, Power BI). Experienced in compliance- driven AI systems (RBI, PCI DSS) and mentoring teams in GenAI architecture, prompt engineering, and deployment best practices to accelerate enterprise adoption.
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