Shehbaz Singh Bhullar
Building at the intersection of software & intelligence.
Hyderabad, Telangana
I’ve always been curious about how things work and how they can be made better. That curiosity led me into software engineering and eventually into the world of AI, where I enjoy turning ideas into working projects, experimenting with new technologies, and learning by building. I’m currently an SDE I at Zapcom, working across the stack on a travel product. From frontend development and backend systems to APIs, databases, and authentication, I’ve been learning what it takes to build reliable, scalable features that solve real-world problems. Beyond my day-to-day work, I explore AI, LLMs, and emerging technologies through hands-on projects and experiments. I’m especially interested in bridging the gap between impressive demos and AI-powered products that are genuinely useful, reliable, and built for real users. I believe great engineering comes from staying curious, questioning assumptions, and constantly looking for better ways to solve problems. I enjoy collaborating with people who share ideas, challenge perspectives, and are excited to build something meaningful. Always curious. Always building. Always learning.
Software Engineer I
Zapcom
- Developed full-stack web features using TypeScript, Next.js, Node.js, Express, and PostgreSQL. Integrated Stripe payments and AWS Cognito authentication with Google and Facebook OAuth, built reusable CMS templates, and collaborated with QA to resolve bugs and maintain code quality through Git and code reviews.
Associate
Zapcom
- Built FitAI as a proof of concept (see Projects), then joined the client platform team in April 2026 contributing to full-stack development.
Research Intern
IIIT SriCity
- Built an AI-driven complaint triage system for banking grievances using active learning and transformer-based NLP on a dataset of approximately 200,000 entries, reducing manual labeling requirements by 68% while improving classification accuracy from 92% to 96%.
FIT-AI Coach is a professional-grade, full-stack MERN application that generates hyper-personalized workout and diet plans using Large Language Models. It features a real-time leaderboard, gamification engine, admin dashboard, and a theme-adaptive UI with offline support.
AIGuardian — AI-Powered Student Growth & Safety Companion
Built an AI-powered student companion that delivers personalized learning support and long-term contextual memory using Memobase and the Gemini API. Architected a real-time, serverless backend with Convex and integrated Twilio WhatsApp notifications to provide progress summaries and enable safety monitoring.
Computer Science with Artificial Intelligence & Machine Learning
Chaitanya Bharathi Institute of Technology
Attendee · Oct 24, 2026