Krishna Vamsi

Transforming Azure support through Agentic Ai

Worked at Toyota as an AI/ML Engineer, building Agentic and GenAI solutions. Developed scalable Python (FastAPI) backends, orchestrated multi-agent systems with LangGraph and MCP, and deployed using Docker and AWS (Lambda, SageMaker). Integrated RAG pipelines, ensured privacy, security, and compliance, and optimized performance for enterprise-grade AI systems.

Worked on KeyBank’s AI-driven customer support and analytics platforms. Built NLP and GenAI systems including classifiers, NER, NLG, and RAG workflows. Integrated chatbots across Slack, WhatsApp, and Messenger. Developed LangChain and LlamaIndex-based agents, fine-tuned LLMs, and implemented guardrails for security. Designed scalable data pipelines on GCP and Dataflow, deploying enterprise-grade AI solutions.

Worked on image processing and ML model development, enhancing training data using OCR, SIFT, and augmentation. Built classifiers with VGG, applied predictive modeling, and optimized workflows with LoRA and QLoRA. Automated tasks using Python, managed data pipelines with AWS S3, and ensured CI/CD and model monitoring. Delivered insights through data analysis and maintained high model accuracy in production.

Contributed to an internship optimizing ML models for Google Search and YouTube recommendations. Built neural networks in TensorFlow, engineered data pipelines with Python and SQL, and applied A/B testing with performance dashboards. Improved inference efficiency and collaborated with teams to enhance ML pipelines while gaining hands-on experience with Google’s scalable AI systems.