Gayathri Kakani
Senior Generative Ai Engineer @Huntington National Bank
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WORK HISTORY
Senior Generative Ai Engineer @Huntington National Bank
Columbus, OH, US
Designed and deployed multi-agent AI systems using LangGraph and LangChain to automate workflows and decision-making for enterprise-scale operations.• Built Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and cognitive search for fast, relevant insights.• Fine-tuned and optimized LLMs (GPT-4 Turbo, LLaMA, Gemini) using LoRA/QLoRA, PEFT, and advanced prompt engineering (CoT, ToT, Few-Shot, ReAct).• Developed real-time model serving APIs using FastAPI and Django, containerized with Docker, and orchestrated on Azure Kubernetes Service (AKS) for low-latency deployment.• Implemented end-to-end MLOps pipelines with Azure ML, Data Factory, Synapse, and MLflow to automate model training, evaluation, and deployment.• Orchestrated high-volume ETL and data pipelines using Azure Event Hubs, Data Factory, and Synapse to support near real-time AI workflows.• Optimized LLM inference performance via model compression, quantization, and GPU acceleration, improving response time and throughput.• Built interactive AI-powered dashboards using React, Power BI, and Azure Web Apps to deliver actionable insights to stakeholders.• Ensured Responsible AI and compliance standards, including rigorous model evaluation with RAGAS and DeepEval metrics.
EDUCATION
RVR&JC COLLEGE OF ENGINEERING
Bachelor of Technology - BTech, Information Technology
University at Albany
Master of Science - MS, Information Science (Data Analytics)
ABOUT GAYATHRI KAKANI
Generative AI Engineer specializing in building, fine-tuning, and deploying large language models (GPT-4, LLaMA, Gemini) for enterprise-scale applications. Experienced in LoRA/QLoRA fine-tuning, multi-agent AI systems (LangChain, LangGraph), RAG frameworks, and developing real-time, low-latency model serving pipelines. Strong background in cloud MLOps (AWS, Azure, GCP), Kubernetes/Docker orchestration, CI/CD, and data engineering (PySpark, SQL/NoSQL). Passionate about delivering scalable, production-ready AI solutions that automate workflows, enhance decision-making, and drive measurable business impact while adhering to Responsible AI standards.
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