Job Posting Title Jr. Systems Engineer (Digital Engineering Process Support)

KBR•Chantilly, VA
•$82,000 - $102,000•Onsite

About The Position

KBR is seeking a Junior Systems Engineer to support a U.S. Space Industry Prime Partner in Chantilly, Virginia. The role supports enterprise-wide adoption of Digital Engineering (DE) processes and methods, including Model-Based Systems Engineering (MBSE), under the supervision of experienced systems engineering professionals. The successful candidate will apprentice with experienced MBSE practitioners and help modernize systems engineering and acquisition processes. The position requires an active TS/SCI clearance with Polygraph. The role involves supporting DE approaches that meet engineering and mission systems analysis (MS&A) process needs; helping technical teams and leadership implement MBSE methods; and supporting enterprise-level approaches that make models, data, and information accessible, interconnected, and structured. The engineer will also support federated modeling across the enterprise and mission partners, follow established MBSE methodology guidelines, and communicate modeling concepts and best practices to stakeholders. KBR employs approximately 37,000 people worldwide, serving customers in more than 85 countries and operating in over 28 countries. The posting describes Trinzic as a planned independent company expected to be created through the spin-off of KBR’s Mission Technology Solutions business in January 2027. Employees who join that business before the spin-off are expected to transition to Trinzic when the separation is complete without needing to reapply. The stated annual compensation range is $82,000–$102,000, with the offer based on the selected candidate’s qualifications and internal parity.

Requirements

  • Current, active TS/SCI clearance with Polygraph.
  • Bachelor’s degree in a STEM discipline; Systems Engineering-related degrees are preferred.
  • Foundational understanding of systems engineering principles and familiarity with Digital Engineering or Model-Based Systems Engineering.
  • Basic understanding of data concepts and technologies such as relational databases, ontology, Unified Architecture Framework (UAF), or Systems Modeling Language (SysML).
  • Strong communication skills and ability to collaborate effectively with teammates and stakeholders.

Nice To Haves

  • Master’s degree in Systems Engineering or a related field.
  • Exposure to MBSE tools or coursework, such as SysML.
  • General awareness of digital industry trends such as Cloud/IaC, Data Analytics, DevSecOps, AWS or Azure, and containerization/microservices.
  • Basic knowledge or academic exposure to satellite or space-based technologies.
  • Familiarity with Operations Research/Systems Analysis concepts.
  • Introductory knowledge of Digital Thread or Digital Twin concepts.
  • Willingness to learn and grow within systems engineering disciplines.

Responsibilities

  • Assist with fulfilling Digital Engineering processes and methods for enterprise-wide adoption, using industry best practices and trends.
  • Support the development and use of MBSE processes for systems engineering and analyses, digital thread frameworks, model portfolios, model quality and review processes, and DE-based acquisition methods.
  • Apprentice to experienced Systems Engineering MBSE practitioners and support modernization of systems engineering and acquisition processes.
  • Deliver foundational digital engineering approaches under supervision to help ensure engineering and MS&A processes are met.
  • Assist technical teams and leadership in implementing MBSE methods and techniques.
  • Assist in developing and supporting enterprise-level digital engineering approaches that make models, data, and information accessible, interconnected, and structured to support organizational goals.
  • Ensure systems engineering and MS&A processes covered in the SOW requirements are followed.
  • Support the federated modeling approach across the enterprise and mission partners.
  • Follow the team’s MBSE modeling methodology guidelines and principles.
  • Communicate modeling concepts and best practices to stakeholders at varying levels.
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