AI Operations Lead

Company Description

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 are seeking a highly qualified AI Operations Lead to lead an interdisciplinary team of systems analysts, computational engineering analysts, and machine learning and artificial intelligence experts. The AI Operations Lead will translate Laboratory operational, policy, and administrative challenges into scalable, data‑driven AI workflows and interface with DOE Enterprise‑wide AI efforts. You will work with your team to identify opportunities for improving efficiencies in engineering and Laboratory processes and lead your team in the development and integration of artificial intelligence tools to help drive measurable improvements.

You and your team will work to address challenges across safety design and analysis, driving efficiencies in administrative process and procedures related to manufacturing, automating analysis workflows, knowledge management and training of domain specialists. Qualified candidates should have in‑depth knowledge of machine learning and artificial intelligence models and toolkits, demonstrated experience in applied research in machine learning, or a complementary scientific discipline providing underlying skills in data analytic techniques, strong understanding of data engineering, excellent organizational and communication skills, and have experience with DOE/NNSA administrative policies and procedures.

This position is in the Computational Engineering Division (CED) within the Engineering Directorate, and you will be supporting programs in the Office of the Director.

• Serve as a trusted advisor on applied AI for operational challenges and lead Laboratory‑wide and interface with DOE Enterprise‑wide applied AI efforts for Laboratory operational applications.
• Translate Lab operational, policy, and administrative challenges into scalable, data‑driven AI workflows and communicate technical concepts and trade‑offs clearly to non‑technical stakeholders.
• Define technical roadmaps for AI adoption aligned with mission, security, and enterprise IT constraints.
• Build, staff, and lead project teams across a diverse portfolio of operational AI applications including working with discipline organizations across the Laboratory to source talent and assemble matrixed, high‑performing, cross‑functional teams.
• Provide technical leadership, mentorship, and oversight for AI engineers, data scientists, and software developers.
• Design and deploy AI‑enabled workflows onto enterprise IT infrastructure in coordination with stakeholders.
• Produce plans for software quality assurance, as applicable.
• Maintain and evolve multiple codebases supporting operational use cases.
• Oversee development, integration, testing, and sustainment of production AI systems, and maintenance of AI tools at multiple classification levels, ensuring secure and reliable access to frontier AI models and other machine learning tools across networks and teams.
• Drive best practices for MLOps, model lifecycle management, and system reliability.
• Partner with Lab policy offices, program organizations, external mission stakeholders, and LivIT leadership to align solutions with mission needs and constraints – developing mitigations and solutions to challenges with Lab leadership as appropriate. This includes working with applicable teams to ensure compliance with cybersecurity, data governance, and classification requirements.
• Perform other duties as assigned.

• Ability to secure and maintain a U.S. DOE Q‑level security clearance which requires U.S. citizenship.
• Bachelor’s degree in Computer Science, Computational Engineering, Applied Statistics, Applied…