Systems Engineer II
About The Position
MMB Solutions is seeking a Systems Engineer II to join its Dayton-area team supporting advanced research and development for the Air Force Research Laboratory (AFRL). The role contributes to MOSAIC (Multi-domain Operations Simulation, Architecture, Integration, and Convergence), a research program focused on making complex test, experimentation, and training environments more intelligent, adaptable, and easier to configure. The work centers on Axioma, MMB's software 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 new capabilities alongside a multidisciplinary team. Work includes connecting cloud infrastructure, communications systems, simulation environments, data pipelines, AI/ML capabilities, and external hardware; translating research objectives into requirements and implementations; integrating software-defined infrastructure; exploring AI-assisted experimentation and orchestration; and participating in testing and demonstrations. The team emphasizes practical solutions, rapid experimentation, working prototypes, iterative development, technical curiosity, ownership, and collaboration.
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; the employer is flexible on years when technical capabilities and demonstrated work support consideration.
- 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
- Experience with Kubernetes, Docker, Helm, Ansible, or infrastructure automation.
- Experience with Model-Based Systems Engineering, SysML, DoDAF, or architecture modeling tools.
- Experience with AI/ML integration, agent-based systems, MCP, or automated workflows.
- Experience with Kafka, MQTT, OpenTelemetry, or distributed data pipelines.
- Experience with modeling and simulation, DIS/HLA, or Live-Virtual-Constructive (LVC) environments.
- Experience with software-defined networking, SDR, RF communications, or 5G/6G systems.
- Experience with 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 develop practical solutions with the team.
- 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.
- Develop and evaluate approaches for translating researcher objectives into structured, executable experiments.
- Explore AI assistance for identifying resources, selecting tools, configuring environments, and interpreting system behavior.
- Support integration of AI agents and structured tool interfaces, including MCP-compatible approaches, in controlled and observable workflows.
- 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.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
