Senior Systems & Mission Engineer (Modeling, Simulation & Wargaming)

Virginia Tech Applied Research Corporation•Arlington, VA

12d

About The Position

VT-ARC is seeking a Senior Systems & Mission Engineer to support mission engineering, analytical wargaming, modeling and simulation, and related systems engineering within its Decision Science Division. The work focuses on contested logistics, maritime sustainment, national mobilization, force generation, reconstitution, and defense industrial-base challenges. The role develops automated analytical workflows that connect mission artifacts and engineering requirements with simulation, agentic AI-assisted analysis, and traceable decision products. This is a hands-on senior technical contributor role that includes conventional systems engineering assignments and may involve serving as the primary developer for defined prototypes and proofs of concept. The engineer independently designs, codes, tests, and demonstrates working models and analytical capabilities, collaborating with data scientists, senior engineers, AI engineers, and developers. As capabilities advance toward production, the role coordinates with additional developers and specialists on hardening, scaling, deployment, and sustainment while maintaining continuity of mission requirements and analytical validation. The proposed duty location is Arlington, Virginia, or the National Capital Region. Onsite attendance and hybrid arrangements will be established according to program, security, and customer requirements. Occasional travel of up to 10% may be required. The position is contingent on a contract award expected to begin execution on or about November 1, 2026. Applicants must be U.S. citizens and hold an active Secret clearance or higher at hire, maintaining it throughout employment; TS/SCI is strongly preferred, and certain programs may require TS/SCI access. The stated annual salary range is $180,000–$220,000.

Requirements

At least 10 years of progressively responsible experience in systems engineering, mission or operational analysis, or related technical work, including direct support to defense or national security missions and independent responsibility for technical deliverables.
Demonstrated application of systems engineering methods, including requirements, architectures, interfaces, traceability, integration and verification/validation planning, and assessment of technical evidence.
Ability to produce usable engineering artifacts beyond mission-analysis studies; a prior Systems Engineer title is not required.
Demonstrated ability to develop, test, debug, document, and maintain software supporting analytical, modeling, simulation, or engineering applications.
Ability to turn requirements and model logic into a functioning prototype, rather than solely configuring existing tools or directing others’ development.
Working proficiency in Python, or proficiency in another relevant programming language with demonstrated ability to become productive in Python quickly; candidates must already be able to write, modify, troubleshoot, and test code.
Ability to structure mission problems, define scenarios and capability dependencies, specify model logic and data needs, evaluate alternatives, and connect operational needs to technical requirements and decision-focused findings.
Hands-on ability to configure and use quantitative models or simulations, prepare and evaluate inputs, assess outputs, and conduct sensitivity analysis.
Familiarity with analytical wargaming, tabletop exercises, simulation-based experimentation, or comparable structured operational analysis, including scenario development, data collection, and synthesis.
Practical familiarity with coding tools and workflows such as code editors or integrated development environments, notebooks, version control (e.g., Git), APIs, debugging, and testing.
Ability to understand, inspect, and verify code and analytical outputs, including AI-generated content when used.
Experience using AWS, or demonstrated ability to quickly learn approved AWS compute and storage environments for running prototypes and analytical workflows; ability to follow access controls and data-handling requirements and coordinate infrastructure needs with specialists.
Working familiarity with agentic AI concepts and ability to implement, or rapidly learn to implement, human-supervised agentic modeling and analytical workflows, including task and agent-role definition, tool use, constraints, evaluation criteria, and output verification.
Ability to connect structured mission artifacts, requirements, and measures with simulation inputs and results; learn new digital engineering and analytical workflows; and preserve traceability between model assumptions, implemented logic, and findings.
Demonstrated ability to work directly with government customers, clarify requirements, facilitate technical discussions, demonstrate working capabilities, deliver clear briefings, and professionally communicate assumptions, limitations, and recommendations.
Self-directed execution and sound technical judgment, including ability to develop a work plan from broad guidance, prioritize tasks, deliver engineering products and working analytical prototypes with limited day-to-day supervision, collaborate across disciplines, and seek decisions or specialist support when needed.
Bachelor’s degree in Systems Engineering, another engineering discipline, Operations Research, Computer Science, or a related technical field, or equivalent technical competence and experience demonstrated through relevant professional work. An engineering degree is not required when equivalence is demonstrated; all candidates must meet the applied experience and technical requirements.
U.S. citizenship.
Active Secret clearance or higher at the time of hire, which must be maintained.

Nice To Haves

Experience using AI coding assistants or agentic development tools to accelerate prototyping, debugging, testing, and documentation, with independent review of generated code and appropriate handling of source code and data.
Experience implementing and evaluating agentic or multi-agent analytical workflows, including agent orchestration, retrieval-augmented analysis, tool/API integration, human review, and traceable evaluation of results.
Advanced Python or analytical automation skills; experience developing custom models, data pipelines, or simulation components, deploying prototype applications in AWS, or transitioning research prototypes to supported software with development teams.
Independent leadership of complete analytical wargames or exercises, including game design, facilitation, adjudication, and after-action analysis.
Experience with MBSE, digital engineering, UML/SysML, DoDAF or similar architecture frameworks, structured model/data exchange, and requirements or configuration management tools.
Experience in contested or maritime logistics, transportation, supply-chain resilience, mobilization, force generation, reconstitution, or defense industrial-base analysis; experience supporting ONR, U.S. Transportation Command, Army, or Joint stakeholders.
Depth in agent-based modeling, system dynamics, discrete-event simulation, Monte Carlo analysis, optimization, or human-machine analytical integration.
Advanced degree in Systems Engineering, Operations Research, Engineering Management, Modeling and Simulation, or a related discipline.
Relevant systems engineering professional certification.
Active TS/SCI clearance or higher.

Responsibilities

Translate sponsor questions and operational needs into mission objectives, study boundaries, requirements, assumptions, and measures of performance and effectiveness.
Develop mission decompositions, mission threads, operational architectures, CONOPS, CONEMPs, and scenarios; organize linked mission artifacts, dependencies, constraints, and measures.
Develop and maintain system requirements, architectures, interface definitions, traceability, and integration and verification/validation plans; assess technical evidence, proposed changes, interoperability, and risk.
Define conceptual models, decision logic, input data, constraints, outputs, and evaluation criteria, and translate them into working prototypes and implementation specifications.
Design, code, test, debug, document, and demonstrate proof-of-concept models, simulation components, data integrations, and analytical applications.
Take prototypes from concept to working implementation and iteratively refine them based on evaluation and sponsor feedback.
Use Python and supporting coding tools to prepare data, automate analytical workflows, configure and run models, and examine results.
Conduct trade studies and sensitivity analyses and assess assumptions, uncertainty, and reproducibility.
Implement, configure, and evaluate human-supervised agentic modeling and AI-assisted analytical workflows, including task decomposition, agent and tool orchestration, approved-data retrieval, experiment setup, and result interrogation.
Verify generated code and findings against requirements, source evidence, and reference cases.
Use approved AWS environments to configure and run prototype applications, execute scripts or models, manage analytical data, and retrieve results; coordinate infrastructure, access, and security needs with specialists.
Develop objectives, scenarios, adjudication or evaluation logic, and data-collection plans for wargames and tabletop exercises; support facilitation and synthesize findings with the study team.
Maintain traceability across mission artifacts, AI/ML-assisted analysis, simulation inputs, assumptions, and findings.
Prepare version-controlled code, test cases, model documentation, and implementation notes to support reproducibility, technical review, and transition of viable prototypes to production teams.
Engage government sponsors and mission stakeholders to clarify requirements, facilitate workshops and expert elicitation, demonstrate prototypes and analytical tools, and brief findings, limitations, and recommendations.
Independently plan and execute assigned technical work, resolve routine issues, identify risks and dependencies early, and elevate decisions appropriately.
Produce engineering artifacts and decision briefs, provide peer review, and coordinate deliverables with program leadership.