About
👋 Hey, I’m Swetha Panthagani — a Generative AI Engineer based in Bengaluru, currently working at TCS. I’m passionate about building AI systems that can do more than just generate text — systems that can reason, retrieve information, use tools, collaborate with other agents, and solve real-world engineering problems. Over the past 3 years, I’ve worked extensively with LLMs, RAG, Agentic AI, and Multi-Agent Systems, building solutions using technologies such as LangGraph, DSPy, MCP, Claude, Azure AI Foundry, and AWS Bedrock Agents. A lot of my work has been focused on applying GenAI to automotive and enterprise engineering. I’ve worked on everything from automated test case generation and requirement traceability to SDLC automation and document-based AI assistants. One of my projects reduced engineering effort by around 82%, while another reduced test case authoring from days to minutes. What I find especially interesting is the challenge of making GenAI systems reliable in the real world. That’s why I’ve spent a significant amount of time working on LLM evaluation, LLM-as-a-Judge, Human-in-the-Loop validation, golden datasets, traceability, error handling, retries, and observability. I enjoy working at the intersection of AI and engineering, especially when there’s a complex problem that can be broken down into intelligent agents and automated workflows. Outside of project work, I like experimenting with new AI technologies, exploring how emerging agentic frameworks work, and continuously learning about where LLMs and AI systems are heading next. I believe we’re moving from AI that simply answers questions to AI that can actually take action and solve problems — and I’m excited to be part of that journey. 🚀 Always happy to connect, exchange ideas, and talk about Generative AI, Agentic AI, RAG, LLMs, and the future of AI engineering.
Work experience
Generative AI Engineer at Tata Consultancy Servicess, Aug 2023 - Present · 3 yrs 3 mos, Bengaluru, Karnataka, India, • Developed and deployed AI assist tools for automated generation of FMEA, Hazard Analysis, and Test Cases using advanced prompt engineering. • Built multi-agent workflows integrating LLMs with OpenAI, Google AI, and AWS Bedrock for enhanced document intelligence. • Created custom retrieval chatbot systems to improve decision-making efficiency by comparing parameters across large documents.
