Bhargava Velpula

About Bhargava Velpula

I am an AI Engineer focused on building practical, production-oriented AI systems using LLMs, RAG, and AI agents.Over the past year, I have been actively designing and developing AI products such as LLM-powered chatbots and automated test case generation systems. My work goes beyond simple prompts — I work with full AI pipelines including API-based LLM integration, token management, embeddings, vector search, and Retrieval-Augmented Generation (RAG).I specialize in building AI agents that can reason over structured and unstructured data, apply rules, and generate consistent, reliable outputs. I have hands-on experience creating multi-agent workflows for tasks like requirement analysis, test case generation, and knowledge-based question answering.My technical stack includes:• LLM APIs and orchestration• RAG pipelines with embeddings and vector databases• AI agents and tool calling• Python automation for data processing and workflows• Prompt design focused on reliability and determinismWhat sets me apart is my engineering-first approach to AI. I focus on clarity, explainability, and real-world usability — building systems that reduce manual effort, improve consistency, and scale across teams rather than demos that work only once.I am currently focused on deepening my expertise in applied AI engineering and looking for opportunities where I can build, improve, and ship AI-powered systems at scale.

Experience

1. Associate

   Cognizant

   Aug 2025 — Present · Hyderabad, IN

   Designed and developed LLM-based chatbots to enable fast, context-aware access to engineering and validation knowledge using RAG pipelines• Built an AI-driven test case generator using agent-based workflows to automatically derive test cases from functional requirements and rules• Implemented AI agents capable of reasoning over structured requirements, applying constraints, and generating consistent test outputs• Developed and integrated embeddings, vector search, and API-based LLM orchestration to improve accuracy and reduce hallucinations• Created Python automation to support data preprocessing, rule evaluation, and end-to-end AI workflow execution• Focused on building reliable, repeatable AI systems applied to real engineering problems rather than one-off demos

Education

• Vaagdevi College of Engineering

  Bachelor’s of Technology, Electrical and Electronics Engineering