Speed Wallet • Full-time

Key Achievements:

• →Built and enhanced a Promo Code system supporting promotional benefits across cryptocurrency transactions, including Send, Swap and Plan Upgrade expanding the platform’s promotional capabilities.
• →Redesigned the Promo Code schema by extracting optional attributes from the core table, reducing nullable fields and improving data organization.
• →Optimized Promo Code eligibility validation by replacing JSON-based storage of thousands of account IDs with a dedicated relational table, enabling indexed lookups and eliminating costly JSON parsing.
• →Automated bulk Promo Code condition creation through AWS S3 presigned URL-based CSV uploads, enabling backend-driven processing and reducing manual administrative effort.
• →Developed Kafka consumers for processing admin-approved Promo Code rewards, automated status transitions through scheduler-driven events running every minute, and CDC consumers for Promo Code and Promo Code Applied events, enabling reliable asynchronous and event-driven processing.

LDCE Placement Cell • Part-time

Key Achievements:

• →Designed relational database schemas and developed scalable backend services for the college placement portal using Node.js, Express.js, PostgreSQL, and Prisma.
• →Built and maintained 40+ REST APIs serving 1,800+ students, supporting profile management, resume uploads, placement applications, and tracking.
• →Implemented JWT-based authentication and role-based access control for students, department TPOs, and central TPOs.
• →Implemented secure media upload and access workflows, along with structured Winston logging for improved maintainability, observability, and traceability.
• →Integrated Amazon SES and a Worker process to automate placement-related email notifications, ensuring timely communication of placement updates and important details to students.
• →Collaborated with the development team on API testing and validation using Postman, improving endpoint reliability and consistency.

Infosys Springboard • Part-time

Key Achievements:

• →Developed an automated Streamlit-based platform that converts full-length videos into engaging short-form reels with minimal manual effort.
• →Integrated OpenAI Whisper for accurate speech-to-text transcription and GPT models for intelligent identification of engaging video segments.
• →Applied prompt engineering techniques to improve GPT-generated timestamps, enabling precise, context-aware segment selection.
• →Built the video processing pipeline using FFmpeg and MoviePy with support for custom resolutions, orientations, and automated clip generation.