Warangal, Telangana, India
I am a Computer Science graduate with a strong foundation in Python, Data Science, and Generative AI. I am passionate about building intelligent, data-driven applications and solving real-world problems using AI and scalable backend systems. I have hands-on experience in developing end-to-end solutions, including CI/CD and ETL pipelines, anomaly detection systems, and AI-powered applications. 🔹 Programming & Development • Python, SQL, TypeScript • React, FastAPI, WebSockets 🔹 AI & Generative AI • Generative AI (GenAI) • LLMs (OpenAI, Gemini) • Retrieval-Augmented Generation (RAG) • LangChain • Vector Databases (FAISS, Qdrant) • Prompt Engineering 🔹 Data Science & Machine Learning • NumPy, Pandas • Machine Learning & Deep Learning (CNN, RNN, LSTM) • Natural Language Processing (NLP) • Statistical Analysis (Hypothesis Testing) 🔹 Data Visualization & Tools • Power BI • Matplotlib, Seaborn I am particularly interested in opportunities in Data Science, AI Engineering, and Generative AI, where I can contribute to building scalable and impactful solutions. Feel free to connect with me for collaborations, opportunities, or discussions around AI and data-driven technologies.
Developed responsive web applications using React.js and TypeScript, enabling real-time monitoring dashboards. Integrated REST APIs and WebSockets to stream live alerts, logs, and performance metrics. Designed and implemented an anomaly detection system to identify abnormal query execution patterns based on execution time and system performance indicators. 🔹 Projects: 1.AI-Powered Multi-Agent System (GenAI) Built a multi-agent system using OpenAI GPT-4 and MCP Agents SDK to dynamically route user queries across domain-specific agents (Math, History, General QA). Implemented guardrails and validation mechanisms to ensure safe and structured AI responses. Integrated external tools (Gmail API, system time services) for real-world task automation. Developed backend using Python, FastAPI, and asyncio for scalable and asynchronous processing. 2.AI-Based Semantic Log Retrieval System Developed a semantic search system using FAISS vector database and sentence-transformers for efficient log retrieval. Processed and indexed 500+ log vectors across multiple indices for similarity-based search. Integrated OpenAI GPT-4.1-mini to generate context-aware summaries from retrieved logs. Enabled faster log analysis and improved debugging efficiency using AI-driven insights.