Professional Focus
I am a Senior AI/ML Engineer with more than 10 years of experience working across enterprise technology, cloud data platforms, data engineering, and artificial intelligence. At MiniMed, I work at the intersection of healthcare technology, data, and AI, helping build secure and scalable solutions that transform complex data into reliable insights and intelligent capabilities.
Enterprise AI & AWS
My current work focuses on enterprise AI and AWS cloud architecture. I have experience working with services such as Amazon Bedrock, SageMaker, Redshift, Glue, Lambda, Step Functions, S3, and DataZone. I contribute to the development of cloud-based data pipelines, analytics platforms, machine-learning workflows, and generative AI solutions, with an emphasis on security, governance, reliability, and operational scalability.
Generative AI & MLOps
I am particularly interested in generative AI, large language models, MLOps, responsible AI, and AI-ready data platforms. My work involves connecting governed enterprise data with practical AI applications while considering access control, model evaluation, monitoring, cost management, and production deployment. My goal is to help move AI initiatives beyond experimentation and toward secure, maintainable, and meaningful enterprise use.
Research & Publications
Beyond my professional work, I contribute to the technology community through research, technical writing, judging, and STEM education. My research interests include healthcare AI, generative AI platforms, data governance, cloud security, scalable LLM inference, and enterprise data architecture. I am also co-authoring Enterprise AI on AWS, a forthcoming book focused on building secure, governed, and production-ready AI systems.
Judging & STEM Leadership
I have served as a technical judge for Technovation Girls and the National TSA Conference, evaluating student projects based on originality, technical execution, feasibility, presentation quality, and real-world impact. I currently serve on the Girls in Technology Committee at Women in Technology (WIT), where I contribute new ideas and support the development and implementation of STEM programs and workshops for students.
Technical Foundation
My broader background in software development, data integration, cloud engineering, and enterprise systems helps me approach AI from an end-to-end perspective. I focus on creating solutions that are not only technically capable, but also secure, reliable, maintainable, and ready for real-world use.