Senior DevOps Engineer - Edge AI & Robotics

About Aptiv

Aptiv is a global technology leader with more than 200,000 employees across 48 countries. We develop advanced software, compute platforms, and intelligent systems that enable autonomous driving, advanced driver‑assistance systems (ADAS), connected mobility, and intelligent infrastructure. Aptiv technology is embedded in millions of vehicles worldwide and powers some of the industry's most advanced automotive platforms.

As part of our expansion into Robotics and Adjacent Markets, Aptiv is developing scalable software and embedded computing platforms for autonomous mobile robots (AMRs), drones, industrial automation, and next‑generation intelligent machines. These platforms combine embedded software, sensing, connectivity, autonomy, safety‑critical systems, and cloud‑connected architectures to enable reliable operation in demanding real‑world environments.

As a Lead
Dev Ops Engineer –
Edge AI & Robotics
, you will design, implement, and operate the automation, infrastructure, and deployment pipelines that enable scalable software delivery for robotics, drones, autonomous mobile robots, and intelligent edge platforms. You will work closely with software, AI/ML, embedded systems, and product teams to improve development productivity, release quality, deployment reliability, and operational visibility across cloud, edge, and embedded environments.

• Design, implement, and maintain CI/CD pipelines for robotics, embedded software, AI/ML, and edge platform development.
• Automate build, test, integration, packaging, release, and deployment workflows across multiple software components and hardware targets.
• Establish scalable release engineering practices including versioning, artifact management, dependency control, and traceability.
• Collaborate with development teams to improve build reliability, pipeline performance, test coverage, and software delivery velocity.
• Develop automation scripts, reusable pipeline templates, and standardized Dev Ops workflows for global engineering teams.
• Support secure software delivery practices including access control, secrets management, dependency scanning, and compliance reporting.
• Drive continuous improvement of development infrastructure, tool chains, and release readiness processes.

• Build and operate development, integration, and deployment infrastructure for cloud, edge, and embedded computing environments.
• Create infrastructure-as-code solutions and automation for reproducible environments, test benches, and deployment targets.
• Support containerized workflows using Docker and orchestration technologies such as Kubernetes where applicable.
• Enable reliable deployment of software artifacts to Linux‑based edge devices, embedded targets, simulation systems, and validation platforms.
• Implement monitoring, logging, and observability practices to improve system visibility, troubleshooting, and operational readiness.

• Partner with software, AI/ML, embedded, systems, and validation teams to define efficient development and integration workflows.
• Improve software quality through automated build verification, unit tests, integration tests, static analysis, and regression testing.
• Support toolchain integration for source control, issue tracking, requirements management, artifact repositories, and test reporting.
• Develop dashboards and reports that provide visibility into pipeline health, release status, build quality, and test results.
• Enable reproducible development environments for local development, CI runners, simulation platforms, and target hardware.
• Support compliance with applicable software development processes,…