Systems Engineer II

MMB Solutions•Dayton, OH
•Onsite

About The Position

MMB Solutions is hiring a Systems Engineer II for its Dayton-area team supporting advanced research and development for the Air Force Research Laboratory (AFRL), including the MOSAIC research program. The role contributes to systems that make test, experimentation, and training environments more intelligent, adaptable, and easier to configure. It involves work with Axioma, MMB’s platform for managing distributed resources, integrating data and control flows, orchestrating software and infrastructure, and supporting AI-assisted experimentation. The engineer will help design, build, integrate, and evaluate capabilities across cloud infrastructure, communications, simulation environments, data pipelines, AI/ML, and external hardware. The work includes developing technical requirements and architecture artifacts, integrating software and infrastructure, exploring AI-assisted experimentation and orchestration, and participating in testing and demonstrations. The position emphasizes practical engineering, prototypes, iterative development, collaboration, and delivering working capabilities.

Requirements

  • Bachelor's degree in Systems Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline, or equivalent relevant experience.
  • Approximately 3–7 years of relevant engineering experience; flexibility is noted for candidates whose technical capabilities and demonstrated work speak for themselves.
  • Experience with systems engineering, software-intensive system development, systems integration, or technical architecture.
  • Working knowledge of Linux, networking, APIs, distributed systems, or cloud-native application environments.
  • Familiarity with scripting or software development using Python, Go, Java, or similar languages.
  • Ability to understand technical requirements, communicate design decisions, and work across engineering disciplines.
  • Experience troubleshooting complex technical problems and delivering functional solutions.
  • U.S. citizenship and ability to meet applicable government security and facility-access requirements.

Nice To Haves

  • Kubernetes, Docker, Helm, Ansible, or infrastructure automation experience.
  • Model-Based Systems Engineering, SysML, DoDAF, or architecture modeling tools.
  • AI/ML integration, agent-based systems, MCP, or automated workflows.
  • Kafka, MQTT, OpenTelemetry, or distributed data pipelines.
  • Modeling and simulation, DIS/HLA, or Live-Virtual-Constructive (LVC) environments.
  • Software-defined networking, SDR, RF communications, or 5G/6G systems.
  • High-performance computing, virtualization, distributed compute, or GPU infrastructure.
  • Experience supporting AFRL, DoD research, or advanced defense technology programs.
  • Current Secret or Top Secret security clearance.

Responsibilities

  • Help design and evolve architectures connecting cloud infrastructure, communications systems, simulation environments, data pipelines, AI/ML capabilities, and external hardware.
  • Translate research objectives into technical requirements, interfaces, system designs, and working implementations.
  • Develop and maintain systems engineering artifacts, architecture models, interface definitions, and technical documentation.
  • Apply MBSE concepts, including SysML and DoDAF approaches, to describe systems, relationships, and expected behavior.
  • Evaluate design alternatives, identify integration challenges, and help develop practical solutions.
  • Work with Kubernetes-based environments, containerized applications, distributed computing resources, and supporting infrastructure.
  • Integrate services, APIs, resource adapters, and orchestration capabilities into the Axioma ecosystem.
  • Connect software platforms with simulation tools, communications systems, network infrastructure, telemetry sources, and physical test resources.
  • Support automation of environment configuration, deployment, observability, and system management.
  • Contribute to integration of high-performance computing, GPU-enabled resources, and cloud-native services.
  • Help develop and evaluate approaches for turning researcher objectives into structured, executable experiments.
  • Explore AI-assisted identification of resources, selection of tools, configuration of environments, and interpretation of system behavior.
  • Support integration of AI agents and structured tool interfaces, including MCP-compatible approaches, in controlled and observable workflows.
  • Help establish methods for capturing system state, configurations, data relationships, and experiment results for reproducibility and evaluation.
  • Evaluate where automation adds value, where human approval is needed, and how to make interactions practical for researchers and operators.
  • Participate in software-based, simulated, laboratory, and operationally representative experimentation.
  • Develop test procedures, integration demonstrations, verification methods, and performance assessments.
  • Troubleshoot integration issues across software, networks, infrastructure, and system interfaces.
  • Work with researchers and engineers to understand needs, prototype solutions, and incorporate feedback.
  • Turn lessons learned into improved architectures, reusable capabilities, and working software.
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