Embedded Systems DevOps Engineer (Engineer Software 4) - 29063

HII's Mission Technologies division•Warren, MI

2d•$117,262 - $145,000•Onsite

About The Position

HII Mission Technologies is seeking a highly skilled Subject Matter Expert (SME) in Embedded Systems DevOps (Software Engineer 4) to support and upskill project teams. The primary goal of this role is to establish modern DevOps practices, design pipeline automation patterns, and drive a cultural pivot toward modernized software engineering. You will serve as a mentor for project teams developing embedded systems for ground vehicle platforms, helping them streamline their development lifecycles and leverage emerging Artificial Intelligence (AI) capabilities. This role is on site in Warren, MI and cannot be done remotely. Come support our work with US Army's Gound Vehicle System Center and join a world class team of groundbreaking scientists and engineers!

Requirements

9 years relevant experience with Bachelors in related field; 7 years relevant experience with Masters in related field; 4 years relevant experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 13 years relevant experience.
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
3+ years of relevant industry experience blending embedded systems engineering with DevOps/Release Engineering.
Ability to obtain and maintain a Secret clearance with the US DoD (US Citizenship Required)
Extensive experience in embedded software development (C, C++, Rust) for complex hardware systems.
Experience with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing environments.
Understanding of safety-critical compliance and quality standards commonly used in automotive or defense ground systems.
Proven expertise in designing and maintaining CI/CD pipelines (gitlab experience is desired).
Strong background in Infrastructure as Code (IaC) and configuration management (e.g., Terraform, Ansible).
Experience with containerization and orchestration (Docker, Kubernetes) and their application in cross-compilation and embedded build environments.
Proficiency in scripting languages used for automation (e.g. Python, Bash).
Proficiency in Linux
Demonstrated ability to lead technical transformations and drive cultural shifts within traditional engineering environments.
Excellent communication skills with the ability to explain complex modern DevOps concepts to teams with legacy workflows.
Experience creating technical documentation, reference architectures, and training materials.
Familiarity with modern AI tools for developers (e.g., LLMs, GitHub Copilot, custom AI agents) and how to securely integrate them into an enterprise CI/CD pipeline.
Forward-thinking mindset with a track record of identifying and evaluating new technologies for process optimization.

Nice To Haves

Familiarity with ground vehicle systems architecture, including common communication protocols (e.g., CAN bus, Ethernet, LIN) and middleware (e.g., ROS, AUTOSAR).
Relevant experience in a Department of War environment.
Familiarity with Department of War and specifically Army Software Modernization Policies.
Secret Clearance with the US DoD

Responsibilities

Establish, document, and maintain DevOps pipeline automation design patterns tailored for embedded systems with software and hardware in the loop testing, ensuring alignment with industry best practices and organizational modernization goals.
Assist project teams in setting up their baseline automation architecture and developing pipelines that leverage standardized design patterns while addressing their specific project constraints.
Mentor local project teams to drive the adoption of DevOps practices. Support a cultural pivot toward modern software engineering practices, helping to upskill and organically grow internal team capabilities.
Act as a senior technical escalation point to assist development teams in debugging, troubleshooting, and maintaining pipeline automation infrastructure when necessary.
Investigate, propose, and implement strategies for embedding AI capabilities into project workflows and pipeline automation to achieve measurable capability and efficiency gains (e.g., AI-assisted code reviews, intelligent test selection, automated debugging).