Hello! I am Mohammed Asaad, a Software Engineer with 6+ years of experience specializing in backend engineering, distributed systems, and cloud-native development.

I work extensively with Java (Spring Boot, Spring MVC, Spring Batch), microservices architecture, Kafka pipelines, and large-scale ETL processing. I build high-performance backend systems that integrate with telecom CRM platforms like Siebel, supporting millions of customer operations.

I also develop AWS cloud solutions (Lambda, S3, EC2, RDS, SNS, SQS) and automate infrastructure using Terraform. Additionally, I build services with Flask/Django and modern UI modules with React.

I enjoy solving complex engineering problems and delivering clean, scalable solutions across distributed systems.

I bring a rare combination of deep backend engineering expertise and a growing foundation in AI/ML ethics, governance, and leadership. With 6+ years building distributed systems, cloud-native infrastructure, and data pipelines at scale, I understand how AI/ML tools must integrate with real production environments — not just in theory, but in practice.

As an AI/ML student at Indiana Wesleyan University, I am building the skills to bridge technical implementation and responsible leadership: evaluating models critically, communicating tradeoffs clearly, and ensuring that AI systems are fair, explainable, and accountable. My goal is to become an engineer who builds AI solutions that organizations can trust and rely on.

This portfolio is designed for technical hiring managers, engineering leaders, and academic evaluators in the software engineering and AI/ML space. It is relevant to anyone looking for a candidate who combines hands-on backend and cloud engineering experience with a principled understanding of machine learning concepts, ethical AI practices, and change leadership.

Whether you are evaluating me for a software engineering role, an AI/ML engineering position, or a graduate academic program, this portfolio demonstrates both the technical depth and the reflective, ethics-driven mindset that modern AI/ML teams need.