Leidos is seeking a lead Systems Engineer experienced in Model Based Systems Engineering (MBSE) methods to lead a team that will support the Air Force Research Lab. This role will explore how future weapons systems enable our future fighting force through defining requirements, architectures, and interfaces for the systems that will then be used in conducting detailed campaign analysis (wargaming) through the use of STORM. MBSE tools such as NoMagic Cameo Systems Modeler (CSM) or IBM Rhapsody/Jazz/Doors will be used to create DODAF, UAF, and or SysML models that will be the basis of simulations of the system as well as managing the requirements. The lead will also conduct wargames and determine loss ratios and quantify the interplay between complex military systems.
- As a Systems Engineering Lead with Leidos, will lead a team of expert Systems Engineers who are proficient in the use of MBSE methodologies and tools in a challenging environment to explore how future weapons perform as part of a larger fighting forces using detailed campaign analysis.
- Exercise existing tools and models and create new models to represent new and emerging systems. This will be a synthesis of MBSE tools like NoMagic CSM and mathematical modeling tools like Matlab.
- Support innovative new weapons and technologies and develop performance models to include in the campaign analysis.
- Perform sensitivity and Reliability analysis against the defined requirements to validate the proposed system.
- Interact with USAF leaders by developing reports and presentations which highlight the effectiveness of new technologies.
- Applicants must be a US Citizen and hold a SECRET clearance
- Applicants must have a BS in Aerospace or Systems Engineering or other closely related field with 12+ years of relevant experience in campaign modeling OR a MS in Aerospace or Systems Engineering with 10+ years of experience.
- The ability to lead a multidisciplinary team is a must
- Experience with using tools such as NoMagic CSM and IBM tool suite to do MBSE modeling. As well as experience with executable SysML simulation capabilities and scripting languages.
- Experience with DODAF/UAF and SysML
- Experience with MBSE methodologies such as Magicgrid, IBM Harmony and their interfacing with Agile development methods.
- Experience in simulation environments such as MATLAB, and the ability to program using Python or C++
- Prior experience using Monte Carlo techniques and statistical analysis
- Demonstrated Experience with MBSE methodologies and simulation
- Preferred candidates will have recent and relevant experience with STORM
- Demonstrated experience with Oracle, MSQL, and/or Microsoft databases
- Experience with stochastics simulations
- Understanding of military CONOPS
Experience with Warfighting simulations with development of model inputs with a focus on USAF operations is desired
External Referral Bonus:Eligible
Potential for Telework:No
Clearance Level Required:Secret
Travel:Yes, 10% of the time
Scheduled Weekly Hours:40
Job Family:Systems Engineering
Leidos is a Fortune 500® information technology, engineering, and science solutions and services leader working to solve the world's toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company's 33,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $10.19 billion for the fiscal year ended December 28, 2018. For more information, visit www.Leidos.com.
Pay and Benefits
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Commitment to Diversity
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.