Senior Cyber Super Intelligence (SI) Engineer

LLNL•Livermore, CA

13d•$175,530 - $267,060•Onsite

About The Position

Lawrence Livermore National Laboratory is hiring Senior Cyber Super Intelligence (SI) Engineers for multiple openings in the Computational Engineering Division, within the Engineering Directorate, supporting Global Security’s Energy and Homeland Security program. The role leads and supports complex projects at the intersection of cybersecurity, operational technology, machine learning, and SI. The work involves developing and deploying methods to emulate adversarial behavior and create tools to defend critical infrastructure systems and Federal networks. Positions will be filled at either the SES.3 or SES.4 level based on knowledge and related experience; additional responsibilities apply at SES.4. The engineer advances cyber capabilities, threat analysis, and mitigation strategies for industrial control systems. The position includes research, adversarial simulation, technical analysis, specialized software and model development, and collaboration with interdisciplinary teams, sponsors, and stakeholders. It also involves identifying emerging threats and opportunities, helping shape technical direction, contributing to proposals and program growth, and mentoring team members. This is a career-indefinite position. It is onsite, as indicated by the posting’s #LI-Onsite tag. The role requires the ability to obtain and maintain a DOE Q-level clearance and SCI access. Q-level clearance requires U.S. citizenship and a federal background investigation; cleared employees are subject to random drug testing. External applicants selected for the position must pass a post-offer, pre-employment drug test.

Requirements

Ability to secure and maintain a U.S. DOE Q-level security clearance; U.S. citizenship is required for Q-level clearance.
Bachelor’s degree in cybersecurity, computer science, information technology, computer engineering, or a related technical field, or an equivalent combination of education and related experience.
Advanced experience leading cybersecurity and/or applied SI research efforts.
Advanced experience building systems with SI tool pipelines and frameworks.
Experience in malware analysis, network analysis, host forensics, or a combination of these areas and related tools.
Ability to communicate technical information across multidisciplinary teams and to non-cyber experts, advise policy management, and collaborate effectively in a team environment.
Advanced knowledge of state-of-the-art technologies in SI and cybersecurity.
Advanced analytical, problem-solving, and decision-making skills for developing creative solutions to complex problems.
Ability to manage concurrent technical tasks with competing priorities, approach difficult problems with enthusiasm and creativity, and change focus when necessary.
Advanced verbal and written communication skills to collaborate with teams, explain technical information to multidisciplinary teams and non-cyber experts, and advise senior management and external sponsors; proficient interpersonal skills.
At the SES.4 level, highly advanced project leadership experience and ability to apply, lead, and develop cutting-edge principles and research, work independently, and manage concurrent technical tasks with competing priorities.
At the SES.4 level, advanced experience creating technical direction and vision, writing research proposals, and/or securing sponsor funding.
At the SES.4 level, significant experience and knowledge in at least one of network protocol analysis, cybersecurity data science, reverse engineering, or operational technology implementation.
At the SES.4 level, highly advanced knowledge and experience developing and applying advanced statistical or machine-learning models and/or LLM tooling.

Nice To Haves

Ability to participate 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 embedded systems, scientific data analysis, systems programming, software engineering, agentic frameworks, and high-performance computing.
Knowledge of and experience with one or more machine-learning techniques, including data science, diffusion models, time-series analysis, deep learning, and large language models.
Experience with industrial control systems software and hardware.
Previous experience working for the Department of Energy, Department of Homeland Security, Department of War, utilities, manufacturing, or a cybersecurity firm.

Responsibilities

Lead and support advanced cybersecurity research using creative and automated methods to identify vulnerabilities, discover malicious behaviors and tools, and improve security for operational technology systems.
Collaborate on technical requirements for data collection and adversarial simulation capabilities at LLNL.
Analyze novel attacks to identify tactics, techniques, and procedures; weaknesses; malicious behavior; and attack vectors, and create repeatable workflows supporting the program mission.
Work with interdisciplinary project scientists and engineers to scope, plan, and formulate modeling and simulation efforts for physical, engineering, and computational systems.
Develop, implement, validate, and document specialized analysis software tools and models, and use them to inform understanding and mitigation of operational-technology threats.
Identify emerging threats and opportunities to enhance cybersecurity capabilities and help shape LLNL’s cybersecurity technical direction.
Engage sponsors and stakeholders to develop program growth opportunities, contribute to research proposals, and align work with mission objectives.
Develop and execute innovative approaches to meet sponsor and project needs amid an evolving threat landscape.
Mentor and collaborate with team members, using technical expertise to attract and retain projects, programs, and funding.
At the SES.4 level, direct technical tasks for highly complex projects; set broad research and project vision and strategy; and influence technical direction for the Laboratory and external stakeholders.
At the SES.4 level, develop innovative solutions to abstract and complex problems, convert ideas into usable algorithms or software modules, and perform in-depth analysis using established methods creatively.
At the SES.4 level, develop new ideas, modify approaches, redefine requirements affecting major Laboratory programs, set high-level goals, and contribute to advances in knowledge.
Perform other duties as assigned.