Model Based Systems Engineer

SAIC

Chantilly (VA)

Presencial

USD 180.000 - 220.000

Jornada completa

Hace 3 días
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Descripción de la vacante

SAIC seeks a Model Based Systems Engineer (MBSE) to support the Prime SETA program within the NRO in Chantilly, VA. You will advance Digital Engineering and MBSE adoption across mission-critical national security systems, collaborating with government leaders, SETA teammates, FFRDC partners, and development contractors.

Key responsibilities include applying MBSE and Digital Engineering to develop mission architectures, requirements, CONOPS, and engineering models; creating and maintaining

Formación

  • Required education combinations with 9+ years experience; advanced degrees acceptable in lieu of years.
  • Active Top Secret/SCI clearance with Polygraph.
  • Experience in MBSE, Digital Engineering, SysML and model-centric approaches for architecture development.
  • Experience with government acquisition processes and Agile development in mission-critical environments.

Responsabilidades

  • Apply MBSE, Digital Engineering, and systems engineering best practices to support the development and modernization of mission-critical ground systems.
  • Develop and refine mission architectures, requirements, CONOPS, and engineering models.
  • Create and maintain digital models supporting architecture development, requirements traceability, technical analysis, and lifecycle management.
  • Champion model-centric engineering approaches to improve rigor, collaboration, and reuse across the enterprise.
  • Support development of acquisition artifacts including SOWs, RFPs, technical requirements, and proposal evaluations.
  • Collaborate across government, SETA, FFRDC, and contractor organizations to define future mission needs and capabilities.
  • Facilitate technical exchanges, architecture reviews, and stakeholder engagements to drive alignment and informed decision-making.
  • Identify and manage dependencies, risks, and integration challenges across multiple programs.

Conocimientos

MBSE
Digital Engineering
SysML
Architecture frameworks
Stakeholder engagement
Briefing skills
Technical leadership

Educación

Bachelor's degree in Engineering, Computer Science, Mathematics, Physics, or related STEM
Master's degree
PhD/JD

Herramientas

SysML

Descripción del empleo

Description

SAIC is seeking a Model Based Systems Engineer (MBSE) to support SAIC's Prime SETA program within the NRO in Chantilly, VA.

In this role, you will help advance Digital Engineering and MBSE adoption across mission-critical national security systems, working alongside government leaders, SETA teammates, FFRDC partners, and development contractors. This is a unique opportunity to influence enterprise architecture, future mission capabilities, and Digital Engineering transformation efforts supporting some of the nation's most important space and intelligence missions.

Key Responsibilities

  • Apply MBSE, Digital Engineering, and systems engineering best practices to support the development and modernization of mission-critical ground systems.
  • Develop and refine mission architectures, requirements, CONOPS, and engineering models that support informed technical and acquisition decisions.
  • Create and maintain digital models supporting architecture development, requirements traceability, technical analysis, and lifecycle management.
  • Champion model-centric engineering approaches to improve engineering rigor, collaboration, and reuse across the enterprise.
  • Support the development of acquisition artifacts, including SOWs, RFPs, technical requirements, and proposal evaluations.
  • Collaborate across government, SETA, FFRDC, and contractor organizations to define future mission needs and technical capabilities.
  • Facilitate technical exchanges, architecture reviews, and stakeholder engagements to drive alignment and informed decision-making.
  • Identify and manage technical, programmatic, and acquisition dependencies, risks, and integration challenges across multiple programs.

Qualifications

Required Education and Experience:

  • Bachelor's degree in Engineering, Computer Science, Mathematics, Physics, or a related STEM discipline and 9+ years of relevant experience; Master's degree and 7+ years; or PhD/JD and 4+ years. Additional relevant experience may be considered in lieu of a degree.
  • Active Top Secret/SCI clearance with Polygraph.
  • Proven hands-on experience developing, building, and executing quantitative models independently, with the ability to balance strategic thinking and stakeholder engagement with direct analytical and modeling execution.
  • Demonstrated experience in Model-Based Systems Engineering (MBSE), Digital Engineering, SysML, and model-centric approaches supporting architecture development, requirements management, and technical baseline control.
  • Experience applying systems engineering principles to the development, integration, and modernization of complex national security, intelligence, space, or defense systems.
  • Experience applying UAF, DoDAF, or comparable architecture frameworks to support system architecture, interface definition, requirements traceability, and engineering decision-making.
  • Experience supporting enterprise and system-of-systems engineering activities, including CONOPS development, cross-program integration, and lifecycle engineering.
  • Knowledge of government acquisition processes, Agile development practices, and software-intensive system delivery within mission-critical environments.
  • Ability to collaborate effectively with government, contractor, FFRDC, and mission partner organizations while providing technical leadership and engineering guidance.
  • Strong written, verbal, analytical, and briefing skills, with experience communicating technical recommendations to senior government stakeholders.
  • Experience supporting NRO, NGA, IC, DoD, or other classified space and intelligence programs preferred.

Target salary range: $180,001 - $220,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.


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