System Engineer (Compute Node)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a System Engineer (Compute Node) based in Ireland.

This is a highly technical, systems-focused engineering role at the core of next-generation AI cloud infrastructure. You will contribute to the design and operation of compute systems that power large-scale virtual machine workloads on GPU-based clusters distributed across multiple data centers. The environment spans virtualization, networking, storage integration, and cluster-scale scheduling, supporting thousands of servers and tens of thousands of GPUs. You will work in a deeply engineering-driven team solving complex infrastructure challenges around performance, scalability, and hardware efficiency. The role combines low-level systems expertise with modern cloud-native technologies such as Kubernetes and virtualization stacks. This is an opportunity to build foundational infrastructure that enables large-scale AI workloads across a global platform.

• Contribute to the design, development, and operation of compute node services managing virtual machines on large-scale GPU-based infrastructure.
• Work on virtualization layers including VM orchestration, scheduling, and integration with storage and high-performance networking systems.
• Develop and optimize systems using Kubernetes, including extending or building components for compute and workload orchestration.
• Support and enhance virtualization technologies such as KubeVirt and QEMU/KVM within distributed environments.
• Work closely with Linux internals, focusing on performance tuning, resource management, and system-level debugging.
• Collaborate on infrastructure that integrates GPU, DPU, and high-performance hardware acceleration technologies.
• Participate in building and maintaining large-scale distributed systems spanning multiple regions and data centers.

Requirements:

• Strong experience with Kubernetes, including not only deployment but also development or extension of platform capabilities.
• Solid understanding of virtualization technologies such as KubeVirt and QEMU/KVM is highly desirable.
• Deep knowledge of Linux systems internals, including process management, system calls, file systems, and performance optimization.
• Familiarity with server hardware architecture, including PCIe devices, NICs, kernel drivers, and system-level components.
• Experience or strong interest in hardware acceleration technologies such as GPUs, DPUs, or ARM architectures.
• Proficiency in at least one of the following languages: Go or C++, with willingness to work across both.
• Strong understanding of concurrency, debugging, profiling, and performance analysis in distributed systems.
• Ability to work in complex, large-scale infrastructure environments and solve low-level systems challenges.
• Curiosity and willingness to learn advanced technologies such as NVIDIA DOCA is a plus.

Benefits:

• Competitive compensation package aligned with senior systems engineering roles.
• Opportunities for career growth and continuous technical learning.
• High level of autonomy, ownership, and technical responsibility.
• Collaborative engineering culture focused on innovation and impact.
• Opportunity to work on cutting-edge AI infrastructure and large-scale GPU systems.
• International team environment with highly skilled engineers.
• Exposure to complex distributed systems at global scale.