Full-Stack Developer Intern with MERN stack, backend API, and AI integration skills.
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Assessing your cultural and operational fit
Final-year B.Tech CSE (AI) student from GITA Autonomous College, Bhubaneswar, graduating April 2026 with a 7.5 CGPA. Comfortable with JavaScript, React, Node.js, MongoDB, REST APIs, and Git. I have shipped real projects using backend services, API integrations, and database design, and I am actively building my full MERN stack skills. Open to onsite work in Bhubaneswar and keen to grow under experienced engineers in a product-focused team.
GITA Autonomous College
B.Tech · Computer Science Engineering (AI)
November 1, 2022 – April 1, 2026
KBRC School
Class XII · Science
March 1, 2020 – March 1, 2022
Multi-Agent Concierge System
June 6, 2026 – Present
Python + JavaScript full-stack system handling restaurant recommendations, activity planning, and bookings — demonstrating backend API design, database integration, and scalable architecture. Built REST API backend with intelligent request routing and load balancing, achieving sub-millisecond agent orchestration. Integrated MongoDB for session persistence, reducing memory overhead by 40% while maintaining sub-300ms API response times. Designed modular backend services following separation-of-concerns principles - directly applicable to Express + Node.js architecture. Participated in code reviews and iterative debugging cycles to improve reliability and performance.
AI Voice Agent Platform
June 6, 2026 – Present
Production-ready conversational web application integrating OpenAI API with a custom backend — demonstrating full-stack thinking, API integration, and frontend-backend communication. Built stateful backend service managing multi-turn conversation context — mirrors session handling in Node.js/Express applications. Integrated third-party AI API with custom prompt engineering, handling authentication, request/response cycles, and error states. Developed frontend UI components with real-time interaction, achieving 85%+ task completion rate in production. Assisted with deployment, debugging, and performance optimisation across the full stack.
E-Commerce Product Pricing - ML Pipeline
June 6, 2026 – Present
End-to-end data pipeline and ML model for predicting e-commerce product prices — showcasing data handling, backend logic, and analytics integration. Processed and cleaned 10,000+ product listings, building a robust data pipeline with an 85/15 train-validation split. Built ensemble ML model achieving 18-22% SMAPE, outperforming baseline by 12% through feature engineering. Delivered visualisations and metric dashboards to track model performance — relevant to analytics and BI integration in web apps.
Cultural Fit Analysis
The candidate's projects demonstrate a diverse skill set across full-stack development, AI integration, and data science, indicating adaptability and a willingness to learn new domains. The stated interest in growing under experienced engineers in a product-focused team suggests a collaborative and growth-oriented mindset. The projects, while academic/personal, show initiative and a drive to build functional systems, which aligns with a proactive culture.
Soft Skills & Operational Fit
The candidate's project descriptions highlight participation in code reviews and iterative debugging, suggesting an ability to collaborate and improve reliability. Their experience with deployment and performance optimization indicates a practical, operational mindset. The focus on product-focused teams and onsite work availability also points to a good operational fit.