Asad M

Optimized AWS infrastructure for a geospatial system, reducing costs by $100k/year. Built AWS-based data pipelines (Lambda, S3, DynamoDB) to process large spatial datasets and prototype LLM-driven automation tools to streamline operations.

Led backend development for Amazon Last Mile logistics, optimizing delivery workflows and real-time forecasting performance. Implemented AWS Lambda and SQS to process millions of delivery events daily and improved observability with CloudWatch metrics and automated alerting.

Built low-latency backend systems for Prime Video Live Events, supporting millions of concurrent users during Thursday Night Football. Implemented event-driven architectures with SQS and Kinesis and scaled services with Kubernetes and AWS EC2 to maintain streaming performance under peak load.

Developed real-time job error fix engines using Apache Flink to improve fault tolerance and resilience in streaming systems. Built an event-driven alpha signal generation platform using high-frequency data streams and improved release stability with Docker and Kubernetes-based deployments.

Led office hours and tutorials for graduate software engineering and concurrent systems courses. Graded assignments, mentored students, and helped refine course materials and technical requirements.

Designed and developed a full-stack ERP to integrate procurement, processing, and sales workflows. Built a demand-forecasting engine achieving 99% fulfillment during seasonal fluctuations and delivered a quality control module with digitized inspection logs and batch traceability.

Built an in-house Android regression testing framework using pytest and Jenkins to streamline app testing workflows. Managed a demo Android app for client demos, improving usability and cross-platform functionality.

Earned an M.S. in Computer Software Engineering at The University of Texas at Austin from 2016 to 2018.

Earned a B.A.Sc. in Computer Software Engineering at The University of Texas at Austin from 2010 to 2013.