Distributed AI Backend & Cloud Infrastructure

Architected and deployed a hybrid infrastructure supporting AI-powered mobile and web applications across both self-hosted and cloud environments.

Designed and deployed infrastructure supporting multi-environment (local + cloud) workloads across AWS and on-prem systems
Built backend systems capable of handling real-time image processing and AI inference pipelines
Developed architecture supporting scalable object storage and dataset management (S3 + MinIO)

Reduced system latency by leveraging hybrid inference (on-device + cloud + GPU acceleration)
Enabled parallel model execution and validation workflows, improving diagnostic reliability
Designed infrastructure capable of scaling from local development to production cloud deployment