AI Infrastructure Engineer – Materials Research Staff Member - Active Clearance Required

Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have an opening for a Materials Research Staff Member to lead the development and institutionalization of advanced data, AI, automation, and digital infrastructure capabilities that accelerate R&D workflows across materials engineering and science environments. You will work at the intersection of materials research, hardware automation, AI, data engineering, cloud and internally hosted computing systems, and institutional data infrastructure, helping define and deploy scalable technical solutions for Lab-wide adoption. You will lead and coordinate multidisciplinary efforts spanning Engineering, Science and Technology, Computing, Enterprise Networking, cybersecurity, and institutional data governance bodies, while collaborating with internal and external partners to modernize how experimental, process, and machine data are captured, governed, integrated, and used for AI-enabled scientific workflows. This position is in the Materials Engineering Division (MED) within the Engineering Directorate. This position requires full-time on-site presence due to the nature of the work. You will Lead the research, design, validation, and transition of advanced R&D data and AI workflow technologies for institutional deployment. Architect and implement integrated technical solutions for scientific data workflows, metadata capture, automation systems, and AI-enabled experimental environments. Develop and drive institutional