Vazeer Ahammad

Designed an automated news curation system that processes RSS feeds and applies NLP-based classification to rank and organize articles. Implemented multi-threaded processing and storage of curated results to enable near-real-time discovery. Reduced manual editorial effort by systematizing ingestion and content selection.

Developed a social image-sharing platform with personalized content feeds and user interaction features. Implemented authentication using Facebook OAuth and built infrastructure supporting real-time user experiences. Added recommendations and session-related mechanisms to improve engagement and content discovery.

Built backend systems for a short-video and AI content platform, focusing on scalable APIs and real-time ingestion/search pipelines. Developed serverless services and performance optimizations to support large daily traffic and creator workflows. Integrated media processing with FFmpeg and added AI-driven text-to-video generation and creator tooling.

Led backend architecture and delivery for a short-video and AI content platform used by tens of millions of users. Built serverless services on AWS Lambda using Node.js and designed GraphQL APIs integrated with the front end. Implemented real-time ingestion and search pipelines using Kafka with Elasticsearch and optimized MongoDB queries for lower latency. Developed notification workflows (APNs/FCM/GCM) and video processing pipelines using FFmpeg, improving engagement and rendering performance.

Developed backend services for social networking and content aggregation products using Java on Google App Engine. Built RESTful APIs and engineered a news aggregation pipeline that parses RSS feeds and applies NLP-based keyword classification, publishing results to Amazon S3. Created supporting social features including Facebook OAuth-based flows, analytics integrations, and mobile application components to support product features.