Damodar Reddy

I’m a Senior AI and MLOps Engineer with 10+ years of end-to-end experience designing and deploying production-grade machine learning, GenAI, and MLOps solutions. I’m U.S. Citizen, translating complex business challenges into scalable, measurable AI-driven outcomes across Healthcare, FinTech, Insurance, Sports Commerce, and Telecom-like environments.

My focus is deep expertise in LLMs, RAG architectures, and agentic workflows using LangChain, LangGraph, and LlamaIndex—grounded in prompt engineering and strong production discipline. I’ve delivered intelligent document processing and conversational AI platforms at enterprise scale, recognized for clean, well-documented, production-ready code and strong cross-functional collaboration.

In my recent work at UnitedHealth Group, I architected a HIPAA-aligned clinical documentation Q&A assistant and improved operational outcomes (for example, reducing physician charting time by 35%). I also built an LLM-driven prior authorization engine, designed agentic eligibility and claims triage workflows, and led HIPAA-compliant data pipelines—then wired the whole system into reliable MLOps with MLflow, monitoring, automated retraining, and containerized deployments.

Earlier, at Fanatics, I built personalization recommendations and real-time demand forecasting, implemented full MLOps frameworks to reduce drift and degradation incidents, and created internal tools and dashboards that streamlined decision-making. At Apollo Global Management and Apollo Hospitals Group, I developed NLP contract/portfolio intelligence systems and prediction pipelines, combining modern LLM/agent patterns with robust data engineering and deployment practices.