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Singanamalla Supraja

Gen AI Developer · Python, LangChain, FastAPI

Bengaluru, Andhra Pradesh, India

@singanamalla_supraja

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About

Gen AI Developer with 3.8 years of experience building enterprise AI applications using LLMs, LangChain, FastAPI, and RAG. Experienced in AI chatbots, natural language SQL assistants, and LLM-powered validation systems with multilingual support, semantic search, prompt engineering, and scalable microservice architectures.

Experience

  • Associate | GenAI Developer
    Cognizant Technology Solutions · Bengaluru, IN
    Dec 2022 – Present

    Developed a GenAI-driven SQL assistant using LangChain and OpenAI that enables users to run database queries through natural language, automating more than 60% of manual reporting and query efforts. Developed a GenAI-powered QnA chatbot using RAG architecture and LangChain that retrieves relevant documents via vector search and generates accurate, context-aware responses. Developed and supported an AI-powered Service Record Quality (SRQ) Validation system that validates field engineers service documentation using LLMs, LangChain, and business validation rules before submission.

Education

  • Bachelor of Technology
    Electronics and Communication Engineering (ECE) · Jun 2018 – May 2022

Skills

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.

Tools / apps / platforms

2 to 5 years 2 to 5 years Several years of experience.
PostgreSQL
<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Kibana Postman Microsoft Azure

Projects

  • SRQ AI Validation System
    Python, LangChain, OpenAI GPT, PostgreSQL, Google Translation API

    AI-powered validation system for reviewing service documentation with multilingual validation, semantic checks, contradiction detection, response caching, and production support.

  • QnA Chatbot using GenAI
    Python, LangChain, RAG Architecture, OpenAI

    GenAI-powered QnA chatbot using RAG to retrieve relevant documents and generate contextual responses with reduced hallucinations and support for follow-up questions.

  • Multilingual AI SQL Chatbot
    Python, LangChain, PostgreSQL, OpenAI

    Multilingual (English/French) conversational assistant for querying relational databases through natural language, with LLM-based translation, intent clarification, secure SELECT-only SQL generation, and Excel export.

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