Summary
Alexis Hernandez is a seasoned software engineer with nine years of experience building large-scale data platforms and security systems, most recently at Microsoft where he doubled threat detection through adversary emulation and low-friction data pipelines. He blends deep data engineering expertise—ETL, streaming, geo-redundant architectures on Azure, Kafka, Databricks—with practical cost and performance optimization to deliver high-value, production-ready assets for SOCs and product teams. Alexis has a track record of driving automation that cuts incident response time by hours and generating multi-million dollar savings through pipeline redesign. He also brings cross-domain experience from device-focused analytics and experimentation frameworks to GenAI financial data pipelines, reflecting a rare mix of security, cloud, and ML-adjacent work. A UTEP-trained computer scientist based in Redmond, he pairs rigorous academic roots with a knack for turning complex telemetry into hyper-actionable detections and business insights.
9 years of coding experience
16 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at The University of Texas at El Paso
Spanish, English