Headline

AI Engineer | Generative AI • LLMs • Agentic AI • RAG | Machine Learning • Deep Learning | LangChain • CrewAI | Python • Streamlit • Docker

About

AI Engineer specializing in Generative AI, Large Language Models (LLMs), and Agentic AI systems. I have hands-on experience building end-to-end AI applications that combine LLMs, Retrieval-Augmented Generation (RAG), and multi-agent architectures using LangChain, LangGraph, and CrewAI. My work focuses on designing intelligent AI agents, orchestrating complex workflows, and delivering scalable AI solutions. Alongside GenAI, I have a strong foundation in Machine Learning and Deep Learning, with experience in CNNs, NLP, and model development using TensorFlow, Keras, and scikit-learn. I also use Docker to containerize and deploy AI applications reliably. 🔹 Core Expertise: • Generative AI & LLMs • Agentic AI & AI Agents • RAG-based systems • LangChain, LangGraph, CrewAI • Machine Learning & Deep Learning (CNNs, NLP) • TensorFlow, Keras, scikit-learn • Python, Streamlit, FastAPI • Docker & AI deployment I am actively seeking full-time roles as a Generative AI Engineer, AI Engineer, Machine Learning Engineer, or LLM Engineer where I can build production-grade AI systems and contribute to real-world impact.

Location

Telangana

Work experience

Generative AI Engineer at Self-Driven Projects, Dec 2025 - Dec 2025 · 1 mo, • Designed and developed a fully AI-powered marketing automation platform using CrewAI’s multi-agent orchestration framework. • Built interactive workflows where autonomous AI agents collaborate to generate end-to-end marketing outputs including strategy plans, content calendars, social media posts, blogs, and short-form video ideas. • Developed a user-facing Streamlit interface that allows users to input product details and instantly receive professional, structured marketing assets. • Integrated Retrieval-Augmented Generation and agent reasoning to automate complex content creation workflows using Large Language Models (LLMs). • Containerized and deployed the application using Docker for scalable execution and included LiteLLM proxy support for efficient local LLM access. • Leveraged Python and CrewAI to enable intelligent task delegation, multi-agent coordination, and automated output generation.

AI Engineer (LLMs & NLP) at Self-Driven Projects, Nov 2025 - Nov 2025 · 1 mo, • Designed and built an AI-powered news research and summarization platform using advanced NLP and LLM techniques to automatically gather, analyze, and summarize current news topics. • Implemented automated web scraping and retrieval pipelines to fetch real-time news, followed by semantic processing and relevance ranking. • Developed an intelligent NLP system that generates concise and contextually accurate summaries using Large Language Models (LLMs) for efficient research workflows. • Built an interactive user interface using Streamlit to allow users to input search parameters and receive organized news insights instantly. • Integrated RAG (Retrieval-Augmented Generation) techniques to enhance information accuracy and topical relevance. • Leveraged Python, NLP libraries, and model workflows to improve processing speed, accuracy, and user experience.

Machine Learning Engineer (Deep Learning) at Self-Driven Projects, Sep 2025 - Sep 2025 · 1 mo, • Designed and developed a deep learning–based plant disease identification system to classify Potato and Tomato leaf diseases from images. • Built and trained Convolutional Neural Network (CNN) models for image classification using TensorFlow and Keras. • Performed image preprocessing, data augmentation, and model optimization to improve prediction accuracy. • Implemented model evaluation and validation techniques to assess performance across multiple disease classes. • Developed an end-to-end ML pipeline from data preparation to model inference. • Focused on real-world agricultural use cases to enable early disease detection and decision support.