Expert Embedded DevOps Engineer

Location: Rostock, Germany
Seniority: Expert
Language: English (required), German (nice to have)

Required Qualifications:

• Expert-level hands-on experience with Jenkins, Git, Linux, and CI/CD pipeline design and optimization.

• Strong understanding of Embedded Linux environments, cross-compilation, and C/C++ software development processes.

• Practical experience with Yocto, BitBake, or similar embedded build frameworks.

• Advanced scripting and automation skills using Python, Bash, and Groovy.

• Hands-on experience with Docker, Ansible, and infrastructure automation.

• Hands-on experience integrating automated testing solutions, including hardware-based testing environments.

• Practical experience with AI/LLM tools in DevOps and software engineering workflows.

• Ability to independently evaluate existing technical solutions, propose improvements, and implement them effectively.

• Very good command of English.

Nice to Have:

• Experience working with IoT, smart metering, or security-sensitive embedded solutions.

• Knowledge of cybersecurity principles, secure software delivery, and certification standards such as BSI or Common Criteria.

• German language skills.

Project Description:

We are looking for an experienced Embedded DevOps Engineer to support the development and continuous improvement of CI/CD infrastructure for embedded Linux solutions.

The role focuses on optimizing build and release processes, enhancing test automation, and ensuring the stability and reliability of development environments. You will work with DevOps technologies, embedded software build systems, and AI-powered tools to streamline engineering workflows and improve overall delivery efficiency.

Scope of Services:

• Develop, enhance, and maintain CI/CD pipelines supporting embedded Linux software development.

• Manage and optimize Jenkins-based build infrastructure and automated release workflows.

• Implement and integrate automated testing solutions, including Hardware-in-the-Loop (HIL) and regression testing.

• Improve the reliability, consistency, and reproducibility of software builds and testing environments.

• Automate infrastructure provisioning and development processes using scripting, containerization, and Infrastructure as Code (IaC) practices.

• Analyze existing engineering workflows, identify performance bottlenecks, and introduce improvements.

• Explore and implement AI-assisted solutions to support test automation, log analysis, troubleshooting, and engineering productivity.