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

Company Description

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.

• 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 standards, frameworks, and infrastructure for AI and automation networking, metadata management, and data lake architectures for the Materials Engineering Division and beyond.
• Resolve complex technical objectives involving competing requirements across scientific workflows, enterprise IT, cybersecurity, data governance, and sponsor needs.
• Serve as a primary technical leader on projects focused on modernizing R&D workflows through data engineering, AI integration, hardware automation, and scalable compute and storage architectures.
• Define technical requirements, system architectures, and implementation strategies that support cross-directorate and cross-site scientific collaboration.
• Collaborate with technical area leaders, project leaders, program management, IT partners, and institutional governance organizations to align solutions with broader Laboratory priorities.
• Represent technical capabilities, architectures, and project outcomes to internal management, institutional leadership, and external sponsors.
• Organize, analyze, and present technical results, adoption outcomes, and workflow impacts from research and development activities.
• Contribute to the conception, design, and execution of innovative projects that advance institutional data and AI capabilities for R&D environments.
• Mentor early-career staff in data engineering, software architecture, automation systems, AI-enabled workflows, and hardware integration.
• Publish research and technical results, present at technical meetings, and contribute to strategic proposals and institutional initiatives.
• Apply technical knowledge and methodologies to guide the successful completion of project and organizational goals, serving as the primary technical contact on tasks and projects.
• Perform other duties as assigned.

• This position requires an active Department of Energy (DOE) Q-level clearance or an active Top Secret clearance issued by another U.S. government agency at the time of hire.
• Bachelor’s degree in Computer Engineering, Materials Science and Engineering, Mechanical Engineering, or a related technical field, or an equivalent combination of…