Senior Cyber AI Engineer

LLNL•Livermore, CA

1d•Onsite

About The Position

Lawrence Livermore National Laboratory (LLNL) is seeking a Senior Cyber AI Engineer to lead efforts in developing advanced cybersecurity techniques and tools for the defense of critical infrastructure systems and Federal networks. This role involves complex projects at the intersection of cybersecurity, operational technology, machine learning, and AI, focusing on emulating adversarial behaviors to create defensive tools for critical U.S. infrastructure. The engineer will drive the evolution of cyber capabilities, threat analysis, and mitigation strategies for industrial control systems. These positions are within the Computational Engineering Division (CED) of the Engineering Directorate, supporting Global Security’s Energy and Homeland Security (E) program. The specific level (SES.3 or SES.4) will be determined by the hiring team based on the candidate's knowledge and experience, with additional responsibilities assigned at the higher level.

Requirements

Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
Bachelor's degree in cybersecurity, computer science, information technology, computer engineering, or related technical field or the equivalent combination of education and related experience.
Advanced experience leading cybersecurity and/or applied AI research efforts.
Advanced experience with building systems with AI tool pipelines and frameworks.
Experience in malware analysis, network analysis, host forensics or some combination of these skill areas and related tools.
Ability to communicate technical information across multi-disciplinary teams and to non-cyber experts, advising policy management, and applying interpersonal skills to collaborate effectively in a team environment.
Advanced knowledge of state-of-the-art technologies in both AI and cybersecurity.
Advanced analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
Ability to effectively manage concurrent technical tasks with competing priorities, along with the demonstrated ability to approach difficult problems with enthusiasm and creativity and to effectively change focus when necessary.
Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information to multi-disciplinary teams and non-cyber experts and advise senior management and/or external sponsors and proficient interpersonal skills.
Highly advanced project leadership experience and ability to apply, lead and develop cutting-edge principles and research, working independently while effectively managing concurrent technical tasks with competing priorities.
Advanced experience creating technical direction and vision, writing research proposals, and/or securing sponsor funding.
Significant experience in and knowledge of at least one of the following subject areas: network protocol analysis, cybersecurity data science, reverse engineering, and/or operational technology implementation.
Highly advanced knowledge and experience in developing and applying advanced statistical/machine learning models and/or LLM tooling.

Nice To Haves

Ability to engage in creative and competitive proposal processes and leverage sponsor relationships to secure new funding.
Master’s degree or PhD with significant focus in cybersecurity, computer science, computer engineering, or data science/machine learning.
Knowledge of one or more of the following disciplines: embedded systems, scientific data analysis, systems programming, software engineering, agentic frameworks, and high-performance computing.
Knowledge of, and experience with, one or more of the following machine learning techniques: data science, diffusion models, time series analysis, deep learning, and large language models.
Experience with industrial control systems software and hardware.
Previous experience working Department of Energy, Department of Homeland Security, Department of War, utilities, manufacturing, or a cybersecurity firm.

Responsibilities

Lead and support advanced cybersecurity-related research projects leveraging creative and automated methods to identify vulnerabilities, discover malicious behaviors and tools, and advance the state of the art in securing operational technology systems.
Collaborate in the development of technical requirements for data collection and adversarial simulation capabilities at LLNL.
Analyze and assess novel attacks to uncover TTPs, potential weaknesses, malicious behavior, and potential attack vectors with the aim of creating repeatable workflows to support the program’s mission.
Work closely with interdisciplinary project scientists and engineers in the scope, planning, and formulating modeling/simulation efforts for physical, engineering, and computational systems.
Develop, implement, validate, and document specialized analysis software tools and models as required and use them to inform understanding and mitigation of threats to operational technology.
Identify emerging threats and opportunities for enhancing cybersecurity capabilities, helping shape the technical direction of LLNL’s cybersecurity initiatives.
Engage with sponsors and stakeholders to develop new program growth opportunities, contribute to research proposals, and ensure alignment with mission objectives.
Drive and execute innovative ideas and approaches to meet sponsor and project needs in a rapidly evolving threat landscape.
Mentor and collaborate with team members, utilizing your technical expertise to attract and retain projects, programs, and funding.
Perform other duties as assigned.
Direct technical tasks for highly complex projects which consistently require the application of creativity and innovation; set broad research/project vision and strategy and influence technical direction for Laboratory and others wielding extensive influence, such as senior management, industrial partners, and policy makers.
Provide highly innovative solutions to abstract complex problems/ideas, convert them into useable algorithms/software modules, and provide solutions that require in-depth analysis of multiple factors and the creative use of established methods.
Develop new ideas, modify approaches, and redefine requirements that significantly impact major Laboratory programs, set high-level goals, and contribute to the revolutionary advancement of knowledge.