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cnu01/README.md

πŸ‘‹ Hi, I'm Srinivas Vallala

AI Engineer | MERN Stack Developer | Full Stack Solutions

πŸ”§ AI Engineer and MERN Stack Developer with 2.8 years of experience in building AI-powered applications and full-stack solutions. Skilled in Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG) systems, AI Agents, and vector database integrations. Proficient in developing end-to-end products using React, Node.js, Express, and MongoDB, seamlessly integrating AI capabilities. With a proven track record of delivering solutions that enhance performance, automation, and user experience.


🌟 About Me

  • πŸ’» Expertise: Full-stack development using MERN stack and AI technologies including RAG systems, NLP, and AI Agents.
  • πŸ”§ AI Focus: Specialized in building intelligent applications with vector databases, model training, and prompt engineering.
  • πŸ“ˆ Achievements:
    • Built RAG systems with 35% improvement in contextual accuracy
    • Developed AI-powered business intelligence suites with 89% prediction accuracy
    • Created AI chatbots enhancing customer engagement by 60%
  • πŸ›‘οΈ Performance Optimization: Implemented advanced caching, aggregations, and queue-based execution achieving 50% faster response times

πŸš€ Technical Skills

Languages Frontend Backend AI/ML Cloud & Tools
JavaScript, Python React, Redux, HTML, CSS Node.js, Express.js RAG Implementation AWS (EC2, S3), MongoDB Atlas
Material-UI, Ant Design FastAPI, REST APIs NLP, Vector Databases Docker, Git, Bitbucket
MongoDB, PostgreSQL MCP, Agents, Model Training Postman
Prompt Engineering

πŸ› οΈ Key Projects

πŸ€– AI-Powered Business Intelligence Suite

  • Tech Stack: XGBoost, Amazon Bedrock, RAG, Vector DB
  • GitHub: πŸ”— View Project
  • Description: Developed comprehensive AI suite with HotLead AI achieving 89% accuracy in conversion prediction and RefereMore AI driving 28% increase in referral conversions
  • Key Achievement: Implemented OneTruth Analytics with real-time anomaly detection, reducing business decision time from 5 days to under 1 day

πŸ’¬ Slack Clone with AI Integration

  • Tech Stack: React, Node.js, Socket.io, Hugging Face, RAG
  • GitHub: πŸ”— View Project
  • Description: Built collaborative platform with Org Brain RAG plugin enabling 80% faster knowledge retrieval and reducing internal query resolution time from hours to minutes
  • Key Achievement: Implemented document processing system with vector search and automatic summarization, improving content discovery efficiency by 65% and boosting team productivity

πŸ’Ό Professional Experience

🏒 Product Engineer | Credit Dharma

Jan 2025 – Mar 2025 | Bengaluru, KA

  • Contributed to building a RAG system that automated property data retrieval through natural language queries, improving contextual accuracy by 35% and enhancing query response efficiency by 40%
  • Built PostgreSQL Playground and automated 15+ key operations and cron jobs for lead revival, error handling, and callback scheduling, processing daily queries and enabling 99% query tracking accuracy
  • Decoupled dashboard system and refactored lead sync processes, optimizing data retrieval for 10,000+ records, reducing latency by 40%, and improving overall system scalability for 50+ concurrent users
  • Designed modular component architecture with 20+ reusable components and integrated an RAG-based chatbot, enhancing development efficiency by 60% while enabling contextual query handling and improving customer engagement

🏒 Software Development Engineer | Decorpot

May 2022 – Sep 2024 | Bengaluru, KA

  • Architected and developed comprehensive ERP & CRM platform from scratch with integrated modules for Quotations, Inventory, Ticketing, Vendor Management, and User Administration
  • Built real-time dashboards and automated cross-departmental workflows, driving 50% productivity gains across Sales, Marketing, Finance, and Operations teams
  • Optimized system performance through API enhancements and backend improvements, implementing pagination, caching, aggregations, and queue-based execution to achieve 50% faster response times
  • Integrated payment systems and implemented security controls, reducing payment processing time by 30% while establishing role-based access controls for secure user experiences
  • Managed AWS infrastructure and developed internal tools, ensuring high availability deployment while building Snag Reporting System that reduced manual follow-ups by 35%

⚑ Fun Fact

I specialize in building intelligent systems that combine the power of AI/ML with full-stack development, creating solutions that not only perform well but also learn and adapt. Always exploring the latest in AI technologies and their practical applications!


πŸ“« Let's Connect

LinkedIn GitHub Portfolio Email

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