We are looking for individuals that demonstrate an understanding of working in partnership with team peers, who engage, advocate, and contribute to building an inclusive culture, and provide expertise to solve challenging problems.
We have multiple openings for Cybersecurity Reverse Engineers with a background in cybersecurity with emphasis on software assurance. You will contribute, provide subject matter expertise and lead research projects in the area of cybersecurity for critical infrastructure systems and civilian networks. You will leverage LLNL’s software assurance capabilities to enhance the security of software and firmware that resides in our critical networks and industrial control systems devices. These positions are programmatically in Global Security’s Energy and Homeland Security (E) Program and administratively will report to the payroll supervisor of the hiring organization.
This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.
In this role you will
- Perform specialized moderately complex to complex static and dynamic analysis of binaries, firmware and source code to find inefficiencies and bugs, Under limited direction.
- Develop and implement new tools for automated software assurance analysis.
- Reverse engineer software, firmware and malware binaries.
- Interpret results of software analysis and ensure validity and security of software and software updates.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.3 level
- Lead multidisciplinary teams in the areas of software assurance for critical infrastructure cyber security, information security, and network security. Continue building LLNL’s software assurance capability.
- Pursue program development opportunities by co-authoring proposals and proposing ideas that will address sponsor needs. Identify program growth opportunities for existing customers, understanding the customer space and needs.
- Present results and provide subject matter expertise across multi-discipline projects engaging with sponsors on a regular basis.
- Master’s degree in computer science, computer engineering, or a related field or the equivalent combination of education and related experience.
- Software engineering experience in C, C++, or Python.
- Comprehensive knowledge of and/or experience in program analysis of source code, binaries, or firmware.
- Experience with hardware or software debuggers and/or with static disassemblers and decompilers.
- Broad knowledge of instruction set architectures, such as ARM, x86/x64, PowerPC and/or MIPS
- Ability to effectively manage concurrent technical tasks with contending priorities, as well as approaching difficult problems with enthusiasm and creativity to change focus when necessary.
- Proficient verbal and written communication skills with the ability to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-cyber experts and the interpersonal skills necessary to effectively collaborate in a team environment.
Additional qualifications at the SES.3 level
- Significant software engineering experience and advanced knowledge of and experience in software assurance.
- Project leadership experience and ability to work independently while effectively managing concurrent technical tasks with competing priorities.
- Experience writing research proposals and securing sponsor funding, with advanced interpersonal, verbal, and written skills necessary to effectively collaborate in a team environment, present and explain technical information, and provide advice to management.
Qualifications We Desire
- Ph.D. degree in computer science, computer engineering, or a related field.
- Understanding of and/or experience in formal verification methods; experience with firmware extraction from devices; and/or experience with industrial control systems software and hardware.
- Knowledge of one or more of the following computer science disciplines: parallel programming, embedded systems, high performance computing, scientific data analysis, machine learning, systems programming, software engineering, and big data technologies.