Shashi Bhushan Sirka

Led a Proof of Concept (POC) for fine-tuning the DeepSeek R1 large language model (LLM) to align with domain-specific tasks, improving model performance and contextual accuracy for targeted use cases. Designed and orchestrated a POC for autonomous agent workflows using LangGraph, RAG pipelines, and Model Context Protocol (MCP) to enable intelligent task decomposition, contextual retrieval, and dynamic execution across enterprise scenarios. Integrated a Retrieval-Augmented Generation (RAG) pipeline to enhance contextual understanding and improve the relevance of information retrieved during agent execution.

Developed an AI-powered Marketing Mix enterprise solution for promotional analytics using React and Flask, improving businesses to maximize ROI through data-driven insights. Developed comprehensive full stack solution with React frontend and Flask APIs that facilitated the creation and visualization of multiple marketing optimization and simulation scenarios, translating complex AI model outputs into intuitive, visually compelling graphs, thereby enabling users to make data-driven decisions regarding marketing strategy effectiveness across diverse models. Developed an AI chatbot using React with Flask integration, implementing LLM & LangChain, to create responsive optimization scenarios enhancing functionality and user engagement. Integrated OAuth2-based SSO for secure and seamless authentication. Enhanced performance by 15-35% with optimized data structures, reduced bundle size by 40%, improved initial load-time and performance score by 30%, and enhanced UX through caching, Webpack chunking, prefetching, lazy loading, and responsive design. Designed and implemented a microservice frontend architecture leveraging React. Collaborated with teams to design and deploy scalable software & mentored interns.

Identified and resolved security vulnerabilities, implemented rate limiters & payload validators. Developed responsive React User Interface to enhance user engagement and built scalable Restful APIs using Flask and Python to ensure seamless communication between the frontend and backend systems.