Teams at Eli Lilly and Company

Lead development of agentic AI systems that autonomously plan, execute, analyze, and optimize laboratory experiments. Build integrations with robotic platforms and analytical instruments, implement closed-loop learning, deploy reliable containerized services, and ensure experiment data supports downstream model training. Own the platform roadmap, reliability, adoption, and technical direction while managing and mentoring a team of scientist-engineers. Collaborate with chemists, biologists, automation engineers, NVIDIA, vendors, and senior R&D leadership.

Engineer agentic AI and automation integrations connecting planning systems with laboratory instruments, robotic platforms, ELN/LIMS, and data pipelines. Build multi-agent workflows with orchestration, state management, tool integration, error recovery, and human oversight. Deploy containerized services using Docker, Kubernetes, Argo, GitOps, and CI/CD. Collaborate with scientists, automation engineers, and NVIDIA researchers to transition prototypes into reliable autonomous experimentation systems for drug discovery.

Build and operate scalable AI and high-performance computing platforms across GPU, cloud, and on-premises environments. Administer Linux, HPC clusters, distributed computing, scheduling, storage, networking, and NVIDIA GPU infrastructure. Automate infrastructure and ML workflows using configuration management and containers, while improving reliability, performance, monitoring, resource utilization, and cost efficiency. Collaborate with scientists, engineers, and infrastructure teams to support large-scale training, inference, and experimentation.