Chandrakant Koneti

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Passionate about building intelligent web solutions and cutting-edge AI applications. Transforming complex problems into elegant, scalable solutions with modern technologies.

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Chandrakant Koneti
Open to Work
Full Stack
AI/ML
Cloud

About Me

As a versatile Full Stack & AI Developer with extensive experience across four innovative tech companies, I excel at building end-to-end solutions from responsive user interfaces to intelligent backend systems. My expertise spans creating intuitive frontend experiences with React and modern JavaScript, architecting scalable backend systems, and integrating cutting-edge AI technologies. I've successfully designed and deployed production-grade solutions handling millions of requests, optimized performance bottlenecks across the full stack, and delivered measurable ROI through intelligent automation and data-driven insights.

Quantifiable Impact

$30K+ Annual cloud cost optimization
10M+ API requests with sub-100ms latency
1TB+ Records indexed in VectorDB pipelines
93.7% AI model accuracy in production

Technical Skills

Languages

Java Python Node.js JavaScript HTML/CSS TypeScript

Frontend

React.js Angular Redux Context API Material-UI Responsive Design

Backend

Spring Boot Spring Security FastAPI Express.js REST APIs GraphQL

Databases

PostgreSQL MongoDB Redis Kafka SQL

Cloud & DevOps

AWS Docker Kubernetes Git GitHub CI/CD

AI/ML

TensorFlow PyTorch OpenAI APIs LangChain LLM Integration RAG

Tools & Others

Jira Webpack NPM Mockito Unit Testing

Professional Experience

Software Engineer Intern

Yottasecure, Inc. · San Jose, CA, US

Jan 2026 - Present
  • Building a role-aware RAG based AI chatbot using AWS Bedrock with Python Lambda orchestration and DynamoDB backed session history to deliver context-aware responses
  • Optimizing VectorDB indexing of 1M+ records of S3 using custom Lambda triggers to chunk and embed data using Titan, and store them in AWS OpenSearch reducing service costs from $50K to $20K/year
  • Developing data pipelines using 4 Lambdas triggered by EventBridge to store 10K+ security records/day in AWS S3 with IaC provisioned through AWS CDK in TypeScript for downstream LLM workflows
Python AWS Bedrock Lambda DynamoDB OpenSearch AWS CDK

Software Engineer Intern

Reva.ai · Remote, United States

May 2025 - Aug 2025
  • Built and deployed 12 Python AWS Lambdas using API Gateway with DynamoDB for multi-tenant config management, eliminating 30GB data across 20+ Kubernetes clusters and saving $2K/year
  • Enhanced reliability of long-running AI workflows by improving Java Spring Boot Temporal service, unifying error handling for 59 activities into 4 standardized types, reducing manual retries by 98%
  • Developed non-blocking customer usage logging in FastAPI-based AI service for LangChain and Amazon Bedrock, streaming to CloudWatch for real-time billing and cutting latency by 120ms
  • Built Python AWS Lambda with Cognito triggers to sync 100% of SSO users (Okta, Microsoft, Google) in real-time to on-prem DBs via custom REST API
  • Owned integration testing with real mock events for Lambdas and Spring Boot services, boosting test speed by 40%
Python FastAPI AWS Lambda Java Spring Boot

Frontend Engineer Intern

RabbitLoader · Remote

Sep 2023 - Dec 2023
  • Led migration of core micro-frontend from React v14 to v18, fixing legacy bugs and preventing regressions in production
  • Optimized application architecture with Redux and load distribution, cutting bundle size from 300MB to 3MB using Webpack, reducing load time from 12s to 3.5s
  • Boosted UI responsiveness by 400% with infinite scroll and lazy loading, delivering components 5× faster using Material-UI
  • Developed mock APIs in Node.js for E2E testing, enabling faster prototyping and reducing QA cycles by 30%
React TypeScript Redux Node.js Material-UI Webpack

Software Developer Intern

Cambridge Technology Enterprises Limited · Hyderabad, India

May 2023 - Jul 2023
  • Built 2 Java Spring Boot microservices to ingest, validate, and serve 2M+/yr medical-diagnosis records
  • Streamed real-time data from Spring service via RabbitMQ to notification service and 2 Kafka topics for ML team analysis, reducing failures by 10GB+ during peak stages
  • Optimized data retrieval with Redis caching, reducing database calls by 65% and latency by 2s/API request
  • Developed integration tests using Mockito, increasing code coverage by 46% and significantly reducing production bugs
Java Spring Boot PostgreSQL MongoDB Redis RabbitMQ Kafka

Education

North Carolina State University

Master of Science in Computer Science

Aug 2024 - May 2026
GPA: 3.60/4.00 Raleigh, NC
Core Coursework
Design & Analysis of Algorithms Software Engineering Machine Learning & Data Analysis Object-Oriented Design Neural Networks Data Science Foundations Human-Computer Interaction Computer Networks Game Engine Foundations
Research Experience
Research Assistant Prof. Ed Gehringer

Utilized NLP techniques to detect design patterns and principles in student code submissions

  • Automated analysis of GitHub pull requests for design feedback
  • Generated comprehensive reports to help students improve coding practices

IIEST Shibpur

Bachelor of Technology in Information Technology

Nov 2020 - Jun 2024
GPA: 8.15/10.00 Kolkata, India
Leadership & Activities
Head of Technical Society

Led and organized multiple technical events and workshops

Event Organizer

Conducted coding competitions and hackathons for 500+ participants

Personal Projects

The Robot Driver Project
Oct 2025 - Present

The Robot Driver - AI Agentic Web Automation Tool

Revolutionary AI-powered web automation platform that transforms natural language prompts into automated browser actions. Built with FastAPI backend and integrated with cutting-edge AI models.

  • Implemented Gemini API integration for intelligent web page analysis and action prediction
  • Containerized the entire application stack with Docker for seamless deployment
  • Optimized response time by 60% through efficient caching and async processing
Python FastAPI Gemini API Playwright MCP Docker
View Code
DrawIt Project
Nov 2023 - Present

DrawIt - Multiplayer Drawing Game

Interactive real-time multiplayer drawing and guessing game supporting multiple concurrent rooms with live canvas synchronization and AI-powered drawing recognition.

  • Implemented real-time multiplayer gameplay using Socket.io supporting 100+ concurrent users
  • Integrated ML5.js for real-time drawing recognition with 85% accuracy
  • Enhanced security with JWT-based authentication and Redis session management
React Redux Socket.io Material-UI ML5.js Redis
View Code
Personal AI Chatbot Project
Mar 2025

Personal AI Chatbot

Intelligent conversational AI system that leverages personal chat history to provide context-aware responses, featuring advanced RAG implementation and memory optimization.

  • Built RAG system with FAISS vector database for efficient context retrieval
  • Optimized token usage by 5x through intelligent context compression
  • Designed efficient message ID-based retrieval system reducing latency by 40%
  • Integrated multiple social media Export APIs for seamless data ingestion
FastAPI React Gemini API FAISS LangChain Material-UI
Live Demo

Let's Connect

Ready to collaborate on your next project?

I'm always excited to work on challenging projects that push the boundaries of technology. Whether you have a project in mind or just want to say hello, feel free to reach out!

Email

chandrakantkonetius@gmail.com

Phone

+1 (984) 374-9958

Location

Raleigh, NC, USA

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