Ahmad Obiedat is a cloud and AI-focused software engineer with over a decade of experience building resilient, high-throughput platforms for enterprises including Amazon, Ford, Nationwide, and JPMorgan Chase. He has architected AWS microservices and data platforms that reduced latency by 38% and enabled ML/GenAI-driven features like personalization and demand forecasting for Amazon Pharmacy. Skilled across front-end SPA frameworks and Java microservices, Ahmad also leads DevSecOps practices—establishing Terraform-backed CI/CD pipelines with zero critical security findings. Based in Dallas, he blends hands-on engineering with strategic product thinking, translating customer-facing PR/FAQ requirements into HLDs/LLDs and production-grade systems. Currently pursuing a Doctor of Engineering in AI/ML, he combines enterprise-scale delivery experience with deepening academic specialization in AI.
10 years of coding experience
11 years of employment as a software developer
Doctor of Engineering (D.Eng.) in Artificial Intelligence & Machine Learning Artificial Intelligence & Machine Learning, Doctor of Engineering (D.Eng.) in Artificial Intelligence & Machine Learning Artificial Intelligence & Machine Learning at The George Washington University
Udacity
Master's degree Computer Science (ARTIFICIAL INTELLIGENCE), Master's degree Computer Science (ARTIFICIAL INTELLIGENCE) at Franklin University
Coding Bootcamp, Coding Bootcamp at Tech Elevator
Bachelor of Science (B.S.) Computer Engineering, Bachelor of Science (B.S.) Computer Engineering at Jordan University of Science and Technology
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