Full Stack Developer — React.js
Full Stack Developer with a 4-month MERN Stack internship and three deployed production applications using React.js, Node.js, Express.js, and MongoDB.
Dyashin Technosoft Pvt Ltd.
Feb 2026 – May 2026 · Bengaluru, India
Completed a structured 4-month MERN Stack training program covering MongoDB, Express.js, React.js, and Node.js; built REST API endpoints and React components for mini-projects; participated in 16+ weekly mentor-led code reviews; learned MongoDB schema design and connected frontend components to backend APIs.
Dyashin Technosoft
4 mos · Bengaluru, Karnataka, India
Developed and maintained responsive web applications using React.js, Node.js, Express.js, and MongoDB. Built reusable React components, integrated RESTful APIs, implemented authentication and database operations, and debugged application issues. Collaborated with the development team using Git/GitHub while following standard software development practices.
B.E., Computer Science and Engineering
Jun 2022 – May 2026
CGPA: 8.1/10
Bachelor of Engineering - BE, Computer Science
Dec 2022 - May 2026
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Jul 2020 - Aug 2022
Developed and deployed a full-stack real-time messaging application with JWT authentication, user discovery, persistent conversations, 7 REST API endpoints, 4 Socket.io event handlers, 3 MongoDB/Mongoose models, Zustand state management, and a responsive React/Tailwind CSS interface.
Architected and deployed a full-stack e-commerce application with 17 REST API endpoints, separate user/admin access control, 3 Mongoose schemas, 11 reusable React components, Context API, Tailwind CSS, 12 seed products, and demo accounts.
Engineered a full CRUD job-application tracker with a four-stage pipeline: Applied, Interview, Offer, and Rejected. Used 8+ reusable React components, a Git feature-branch workflow, and a persistent JSON file database.
Built an AI-powered interview preparation platform that helps candidates practice technical interviews through personalized questions, interactive interview sessions, and AI-driven feedback. Developing the platform with React.js, Node.js, Express.js, MongoDB, and Generative AI/LLMs. The application focuses on creating realistic interview experiences, generating relevant questions based on the candidate's role and skills, evaluating responses, and providing actionable feedback to improve interview performance. Key areas include AI-powered question generation, personalized interview sessions, response evaluation, feedback generation, user authentication, and interview progress tracking.
Built a real-time chat application using the MERN stack, enabling users to communicate instantly through a responsive and interactive messaging interface. - Developed the frontend using React.js and managed application state with Redux. - Built RESTful APIs using Node.js and Express.js for user authentication, conversations, and messages. - Integrated Socket.IO to enable real-time messaging and online-user status. - Used MongoDB to store user, conversation, and message data. - Implemented features such as user authentication, user search, real-time messaging, online status, and persistent chat history. - Used Git/GitHub for version control and project development.