Rohith Annadurai

About Rohith Annadurai

I’m an AI Data Engineer with hands-on experience designing, fine-tuning, and deploying Generative AI and LLM-driven systems. My work focuses on LangChain, LangGraph, and RAG architectures that bridge conversational AI and data pipelines.I’ve developed end-to-end AI solutions integrating OpenAI APIs, FastAPI, Databricks, and AWS, ensuring scalable, reliable, and low-latency model operations. My recent work involves LLMOps and multi-agent orchestration using Semantic Kernel and CrewAI, enabling adaptive, context-aware automation.Passionate about ethical, privacy-first AI, I strive to create systems that balance intelligence with trust. Open to opportunities in AI Engineering, GenAI Systems, or Applied ML roles, where I can contribute to building innovative and responsible AI products.Skills: Python | LangChain | LangGraph | RAG | FastAPI | Databricks | AWS | vLLM | Semantic Kernel | MLOps | Data Engineering

Experience

1. Ai Data Engineer

   Cloudquestit

   Sep 2025 — Present · Dallas, TX, US

   As an AI Developer, I architected and deployed a production-grade conversational AI chatbot powered by OpenAI GPT models and Python, integrated with Twilio to deliver intelligent property recommendations for daily users. The system provided seamless real-time responses and personalized suggestions, driving high user engagement and satisfaction.I implemented advanced prompt engineering and few-shot learning techniques that improved conversational accuracy by 35% while significantly reducing hallucinations, ensuring a more natural and context-aware interaction flow.To enhance personalization, I developed a machine learning recommendation engine using collaborative filtering and content-based algorithms, achieving 78% prediction accuracy and sub-second inference latency.I engineered scalable data ingestion and validation pipelines in Databricks (PySpark) to process over property listings weekly, automating data enrichment, anomaly detection, and quality assurance cutting manual review time by 70% and improving data reliability by 92%.On the backend, I designed a high-performance data architecture leveraging MongoDB for property metadata and Redis for session management, ensuring smooth performance across concurrent sessions.Additionally, I centralized analytics in Snowflake, integrating Zapier and Zoho Sign for real-time reporting and automated business workflows reducing manual operations by 80%.The system was deployed on AWS (S3, EMR) for scalable data processing, with optimized PySpark ETL pipelines built on MapReduce principles for efficient large-scale transformations.

Education

• University of North Texas

  MASTERS IN COMPUTER SCIENCE

• Auroras Technological and Research Institute (ATRI)

  Bachelor of Technology - BTech, Electronics and Communications Engineering

• Narayana Junior College - India

  INTERMEDIATE, MPC (Math,Physics,Chemistry)