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Full Stack Engineer with less than a year in Web Development & AI.
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Assessing your cultural and operational fit
Nallamalli Siva Sai is an aspiring Full Stack Developer with hands-on experience in building scalable web applications and integrating AI functionalities. With a strong foundation in programming languages like C++ and JavaScript, and expertise in frameworks such as React.js and Node.js, Siva Sai has successfully delivered projects involving real-time data processing, secure authentication, and AI-powered features like Retrieval-Augmented Generation (RAG). Having completed a Full-Stack Developer Internship and contributed to several innovative AI-powered projects, Siva Sai is eager to leverage technical skills and problem-solving abilities in a dynamic engineering environment.
National Institute of Technology Durgapur
B.Tech · Electronics and Communication Engineering
August 1, 2022 – June 30, 2026
BYND
Full-Stack Developer Intern
November 1, 2025 – December 31, 2025
India
PolyMail – AI-Powered Email Assistant
June 28, 2026 – Present
Developed a full-stack AI-powered application enabling users to compose and send emails automatically via Google OAuth (Firebase Authentication). Manual Compose: Integrated AI-powered SmartTouch feature to auto-correct grammar and spelling, with a confirmation dialog before sending via Nodemailer. Prompt-to-Email: Built a natural language processing pipeline using LangChain to extract recipient, subject, and message from user prompts, rewrite content, and dispatch emails after confirmation. Voice-to-Email: Implemented speech-to-text conversion pipeline that transforms voice input into structured emails using AI, with automatic sending after user confirmation. Achieved end-to-end automation with secure OAuth2 authentication, reducing email composition time significantly.
Neuro-Nest – AI-Powered Collaborative Student Dashboard
June 28, 2026 – Present
Developed a collaborative full-stack platform where users can create and join study rooms, and upload study materials to AWS S3 cloud storage. Integrated real-time PDF discussions and live chat features using WebSockets, enabling seamless collaboration and knowledge exchange among students. Built an AI-powered chatbot leveraging Retrieval-Augmented Generation (RAG) with Pinecone vector database to answer queries based on uploaded documents. Implemented real-time file synchronization and discussion updates using secure JWT authentication and room-based access control. Reduced information retrieval time by enabling context-aware AI responses over user-uploaded study materials.
Cultural Fit Analysis
The candidate's projects show a strong inclination towards innovative, AI-driven solutions, which aligns well with forward-thinking technical cultures. The diversity of projects (collaborative dashboard, AI email assistant, design submission platform) indicates adaptability and a broad interest in different problem domains. The academic background in Electronics and Communication Engineering, combined with self-driven software projects, suggests a strong learning aptitude and a proactive approach to skill development.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations like device fingerprinting and AI-powered email automation. The collaborative nature of the 'Neuro-Nest' project suggests good teamwork potential. The detailed project descriptions indicate an ability to articulate technical concepts clearly.