Architect and lead development of agentic AI systems for scientific research, including multi-agent orchestration, tool-use and retrieval infrastructure, model serving and evaluation pipelines, and the abstractions that let LLM-driven agents reliably perform data wrangling, visualization, and analysis. Provide technical leadership, mentoring, and training for software engineers, graduate students, and undergraduate researchers, including code review, architectural guidance, and establishing shared engineering conventions.