Tejaswi V

Senior Ai Ml Engineer - Data & Intelligent Systems @UnitedHealth Group

Minnetonka, MN, US

Designed and delivered end-to-end AI and ML data pipelines supporting advanced analytics, predictive modeling, and LLM-driven applications, with a strong focus on scalability, reliability, and real-world business outcomes.Built and maintained production-grade data ingestion and transformation pipelines using Python, SQL, PySpark, and Spark-based frameworks to normalize and prepare high-volume data from enterprise systems, including transactional, operational, and event-driven sources.Led feature engineering workflows for both structured and semi-structured datasets, enabling data scientists and ML models to operate on high-quality, well-governed features across batch and near–real-time environments.Developed and operationalized machine learning pipelines supporting the full model lifecycle—data ingestion, feature generation, training, validation, deployment, and monitoring—using MLflow, containerized services, and cloud-native orchestration tools.Designed and deployed NLP and LLM-powered solutions, including intelligent assistants and analytical agents, enabling business users to interact with complex datasets through natural language queries and receive actionable insights.Applied prompt engineering and LLM optimization techniques to improve response accuracy, contextual understanding, and domain relevance for merchant- and operations-focused use cases.Implemented agentic workflows leveraging modern frameworks (e.g, LangChain-style orchestration patterns) to enable tool-based reasoning, dynamic data retrieval, and multi-step analytical tasks.Built retrieval-augmented generation (RAG) architectures, integrating vectorized enterprise data sources and search services to improve LLM accuracy, reduce hallucinations, and ensure grounded, explainable outputs.Developed API-first AI services using FastAPI to expose model inference, chatbot interactions, and analytical workflows, enabling seamless integration with downstream applications and dashboards.

MallaReddy Engineering College for Women

Computer Science