The role involves implementing and monitoring security controls across Kubernetes, Linux, and database environments while developing AI-driven security tooling. You will also be responsible for vulnerability scanning, maintaining security documentation, and preparing reports for security reviews.
You will build and maintain the retrieval and knowledge layer for AI systems supporting rare disease research, including modeling biomedical knowledge and tuning search performance. Additionally, you will develop user interfaces, manage deployment pipelines on Kubernetes, and evaluate system performance to ensure clinical relevance.
Build and maintain agentic AI systems for rare disease research workflows, ensuring reliable, validated, and traceable outputs. Collaborate with NIH investigators to design data models and contribute to scientific manuscripts and conference presentations.
The Associate Director will lead multidisciplinary teams in data engineering, AI/ML, and scientific computing to build durable, reproducible research systems. They are responsible for setting technical strategy, establishing operational standards, and bridging the gap between research prototypes and reliable production capabilities.
