Moeiz Shahzad

Architected and implemented a custom automation orchestration environment for durable execution of complex node-based workflows. Engineered a proprietary Workflow Builder engine that translates natural language prompts into executable workflows, and developed scalable micro-services using FastAPI, Blacksheep, MongoDB, and Temporal.

Worked on end-to-end delivery of enterprise-grade backend systems, managing the full product lifecycle from requirement gathering to production deployment. Architected and optimized scalable server-side infrastructures using Frappe and ERPNext, and configured Nginx for reverse proxying and load balancing.

Led the evolution of CropSight into a production-grade Farm Management and Precision Agriculture platform. Architected a high-performance spatial backend using Django, FastAPI, Sentinel and PostgreSQL, and engineered an automated Remote Sensing pipeline using Google Earth Engine and Sentinel Hub API.

Grade: Gold Medalist

Activities and societies: Dean's Award, Merit Scholarship

Pursued a Bachelor's in Computer Science with specialization courses in Machine Learning, Deep Learning, Computer Vision, and Artificial Intelligence. Graduated as Gold Medalist for securing the 1st position in the batch and received a full merit-based scholarship.