Mohit Verma.
Intern
Highly motivated and detail-oriented software developer with experience in building scalable and efficient systems. Proficient in a range of programming languages, including Java, C++, JavaScript, and TypeScript. Strong understanding of system design, microservices architecture, and event-driven systems.
Work Experience
Summer Intern
Board Infinity
Built and productionized a Library Management System supporting 1,000+ books and 100 concurrent users using Core Java. Enhanced search functionality by integrating optimized data structures, leading to a 40% improvement in query latency and reducing database load by 15% during peak seasons. Reworked core execution paths to reduce algorithmic complexity by ~30%, increasing end-to-end request throughput.
Skills
Projects
Event-driven Microservices Commerce Platform
Orchestrated a microservices architecture with 10+ isolated services deployed via Docker containers on AWS EC2, supporting 3 subdomain-based clients and 100+ concurrent sessions. Streamed 50+ user interaction events/session through Apache Kafka, batching events every 3 seconds before persistence to MongoDB, reducing direct write load by ~60% while enabling large-scale behavioral analytics.
Microservices-Based AI-Powered Job Platform
Implemented an event-driven messaging pipeline using Kafka for critical email notifications, including password resets and application status updates, achieving a 42% reduction in synchronous request latency. Designed and optimized PostgreSQL relational schemas with transactions, constraints, and cascading deletes, ensuring ACID consistency during concurrent job applications and recruiter workflows.
Realtime Collaborative Whiteboard
Structured a monorepo architecture with separate HTTP and WebSocket services, implementing JWT-based authentication for REST APIs and WebSocket handshakes, supporting 50+ concurrent users per session with sub-100 ms message latency. Established event-based real-time synchronization, broadcasting drawing operations instead of pixels, reducing network payload size by ~85% and ensuring consistent canvas state across all collaborators.
Education
B. Tech CSE
Lovely Professional University
CGPA: 8.15
Class 12th
Saraswati Vidya Mandir
Percentage: 82%