Kshithesh A

About Kshithesh A

I’m an AI & ML Engineer with 5+ years of experience building Agentic AI systems, LLM-powered applications, and Retrieval-Augmented Generation (RAG) pipelines that drive real-world impact.Currently at CVS Health, I design and deploy autonomous, multi-agent AI frameworks that combine reasoning, memory, and tool use to enable adaptive decision-making. My expertise spans Generative AI, MLOps, and LLM fine-tuning using tools like LangChain, Hugging Face, OpenAI, and Azure OpenAI.I’m passionate about developing scalable, responsible AI systems — optimizing performance with LoRA, PEFT, and quantization, while ensuring reliability across AWS, Azure, and GCP. Beyond engineering, I enjoy exploring how autonomous agents and RAG architectures can enhance human productivity and transform intelligent automation.Always open to connecting with others who share an interest in Agentic AI, Generative AI, and next-gen machine intelligence.Contact : k••••••••@gmail.com | 84••••••83

Experience

1. Agentic Ai Developer

   CVS Health

   Aug 2024 — Present · Woonsocket, RI, US

   Designed and deployed agentic AI systems integrating autonomous reasoning, memory, and multi-step tool use for adaptive decision-making.• Built multi-agent coordination frameworks (LangChain, CrewAI, AutoGen) for collaborative reasoning and dynamic task planning.• Developed LLM-powered agents with RAG pipelines, API orchestration, and retrieval-based reasoning for enterprise data solutions.• Fine-tuned ReAct and Reflexion-style agents to enhance reasoning accuracy, adaptability, and performance in real-world workflows.• Engineered multimodal LLM/VLM architectures using Hugging Face, PyTorch, and OpenAI APIs for text–image generation and analysis.• Implemented RAG systems with vector databases (Pinecone, FAISS, Weaviate) to boost factual consistency and contextual relevance.• Deployed LLM copilots, chatbots, and autonomous assistants with safety guardrails, policy-based moderation, and performance monitoring.• Led MLOps and optimization efforts using Docker, Kubernetes, Ray, and MLflow with LoRA, PEFT, and quantization for scalable deployment.

Education

• Marist University

  masters , Computer/Information Technology Administration and Management