Senior DevOps Engineer - Edge AI & Robotics

Job summary

The Lead DevOps Engineer – Edge AI & Robotics is responsible for designing and implementing automation and deployment pipelines to facilitate scalable software delivery for robotics and intelligent edge platforms. This role involves maintaining CI/CD pipelines, automating workflows, and collaborating with software and AI/ML teams to enhance development productivity and software quality using technologies such as Docker and Kubernetes.

Qualifications

• 3-5 years of experience in DevOps, CI/CD, or platform engineering.
• Experience building and maintaining CI/CD pipelines using tools like GitHub Actions or Jenkins.
• Strong experience with Linux environments and automation.
• Experience with Docker and containerized development workflows.
• Experience with infrastructure-as-code and automated environment provisioning.
• Proficiency in scripting languages such as Python and Bash.
• Understanding of software engineering principles and testing workflows.
• Strong troubleshooting and communication skills.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for robotics and edge platform development.
• Automate build, test, integration, packaging, release, and deployment workflows.
• Establish scalable release engineering practices including versioning and artifact management.
• Collaborate with development teams to improve build reliability and software delivery velocity.
• Develop automation scripts and standardized DevOps workflows.
• Support secure software delivery practices including access control and compliance reporting.
• Drive continuous improvement of development infrastructure and toolchains.
• Build and operate development infrastructure for cloud and embedded environments.
• Create infrastructure-as-code solutions for reproducible environments.
• Support containerized workflows using Docker and Kubernetes.
• Implement monitoring and observability practices for system visibility.
• Partner with teams to define efficient development workflows.
• Improve software quality through automated testing and static analysis.
• Support toolchain integration for source control and test reporting.
• Develop dashboards for pipeline health and release status.
• Enable reproducible development environments for local development.
• Support compliance with software development processes and quality standards.
• Troubleshoot build and deployment issues across engineering teams.
• Support deployment workflows for AMRs and drones.
• Automate packaging and deployment of robotics software and AI/ML models.

Skills

Degrees

Relocation