About You: You are a senior systems thinker and mission engineer with a strong foundation in applied systems engineering. You understand how people, processes, technologies, interfaces, and operational constraints interact to produce mission outcomes. You translate complex defense and national security problems into mission threads, requirements, architectures, analytical models, and evidence-based recommendations.
You are a self-starter who turns broad sponsor guidance into a practical work plan and delivers substantive results with limited day-to-day direction. You engage directly with government stakeholders, ask informed questions, communicate technical findings clearly, and follow through on commitments. You can move between mission-level analysis and practical systems engineering while recognizing when specialist support or a sponsor decision is needed.
You bring hands-on M&S-development capabilities and can quickly turn a conceptual model or framework into a functioning prototype. You use Python and approved cloud environments such as AWS, or can rapidly become productive in them by building on demonstrated development experience. You apply these skills to agentic modeling, simulation, and wargaming, critically evaluating model logic, generated code, assumptions, and outputs rather than accepting them at face value.
Position Overview: VT-ARC is seeking a Senior Systems & Mission Engineer (Modeling, Simulation & Wargaming) to support mission engineering, analytical wargaming, modeling and simulation, and related systems engineering efforts within the Decision Science Division (DSD).
This opportunity focuses on contested logistics, maritime sustainment, national mobilization, force generation, reconstitution, and defense industrial-base challenges. The role develops and refines automated analytical workflows, connecting structured mission artifacts and engineering requirements with simulation, agentic AI-assisted analysis, and traceable decision products.
This hands-on senior technical contributor also supports conventional systems engineering assignments and may serve as the primary developer for defined prototypes and proofs of concept. The individual will independently design, code, test, and demonstrate working models and analytical capabilities while collaborating with data scientists, senior engineers, AI engineers, and developers. As capabilities advance toward production, the role will work with additional developers and specialists on software hardening, scaling, deployment, and sustainment, while maintaining continuity of mission requirements and analytical validation.
This position is a contingency hire based on a contract award expected to begin execution on or about November 01 st , 2026. Duties/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, concepts of operations (CONOPS), concepts of employment (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; translate this structure into working prototypes and implementation specifications that support testing, collaboration, and further development.
- Design, code, test, debug, document, and demonstrate proof-of-concept models, simulation components, data integrations, and analytical applications. Take defined prototypes from an initial concept to a 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; check 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 requirements 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 directly with government sponsors and mission stakeholders to clarify requirements, facilitate workshops and expert elicitation, demonstrate working 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.
Required Education, Certification, Skills, Capabilities: - 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: 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, not solely configure existing tools or direct development by others.
- Working proficiency in Python, or proficiency in another relevant programming language with demonstrated ability to quickly become productive in Python. Candidates must already be able to write, modify, troubleshoot, and test code; prior development experience and successful technical learning are required.
- 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 to use approved AWS compute and storage environments to run prototypes and analytical workflows. Ability to follow applicable 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 verification of outputs.
- 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 communicate assumptions, limitations, and recommendations professionally.
- Self-directed execution and sound technical judgment: 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 above.
Desired Education, Certification, Skills, Capabilities: - 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 model-based systems engineering (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.
Primary Work Location: Proposed duty location is Arlington, VA / the National Capital Region. Onsite attendance and hybrid work arrangements will be established based on program, security, and customer-unique requirements.
Special Work Conditions: Occasional travel (up to 10%) may be required for stakeholder engagements, workshops, wargames, technical reviews, and integration or test activities.
Security: - Must be a U.S. citizen.
- An active Secret clearance or higher is required at the time of hire and must be maintained.
- Active TS/SCI is strongly preferred.
- Candidates selected for certain programs may be required to obtain and maintain TS/SCI access.
Competitive Salary: VT-ARC offers competitive pay based on a number of factors, including but not limited to conducting comparable salary market research, education, years of experience, and benefits.
Salary Range: $180,000• $220,000 annually
