Senior Site Reliability Engineer (SRE, Compute Node Team)

Team: IT

Location: Netherlands

Commitment: Full-time

Workplace Type: remote

Accountabilities

The Senior Site Reliability Engineer will be responsible for maintaining and improving the reliability of compute infrastructure, with a strong focus on Linux systems, virtualization, and operational excellence.

• Ensure the reliability, availability, and performance of compute nodes running virtual machines across cloud environments.
• Analyze and troubleshoot complex Linux systems across both user space and kernel space.
• Investigate and resolve production issues involving CPU, memory, NUMA, cgroups, scheduling, and system performance.
• Work hands-on with virtualization technologies, including QEMU/KVM and Linux-native virtualization solutions.
• Design and improve observability capabilities at the infrastructure layer, including metrics, logs, traces, alerts, SLIs, and SLOs.
• Lead incident response activities, perform root-cause analysis, and drive post-incident improvements.
• Collaborate with platform, kernel, hypervisor, GPU, and infrastructure teams to improve system architecture and operational reliability.
• Develop solutions that enhance scalability, performance, and maintainability of compute platforms.
• Contribute to engineering practices that promote automation, reliability, and continuous improvement.

Requirements:

The ideal candidate has extensive experience in site reliability engineering, Linux infrastructure, and distributed systems, with a strong ability to debug and optimize complex production environments.

• Deep expertise in Linux systems, including user space, kernel space, and core kernel subsystems such as scheduling, memory management, filesystems, cgroups, and namespaces.
• Strong understanding of system architecture, boundaries, and performance trade-offs across different infrastructure layers.
• Hands-on experience with virtualization technologies, particularly QEMU/KVM, including VM lifecycle management and performance optimization.
• Practical experience with container technologies, namespaces, and resource isolation mechanisms.
• Strong debugging and problem-solving skills with a structured, hypothesis-driven approach to incident investigation.
• Solid understanding of SRE principles, including reliability engineering, system design, and operational ownership.
• Experience building and operating observability solutions rather than only consuming monitoring tools.
• Ability to translate system behavior into actionable reliability improvements.
• Experience with Kubernetes internals, node-level components, or large-scale compute platforms is a plus.
• Familiarity with low-level Linux debugging tools such as perf, eBPF, ftrace, strace, or kernel crash analysis is beneficial.
• Experience with hardware-level debugging, GPU infrastructure, NVLink, InfiniBand, or open-source infrastructure projects is considered an advantage.

Benefits:

• Competitive compensation package.
• Flexible working environment with ownership over projects and responsibilities.
• Opportunities for career growth and continuous learning.
• Chance to work on impactful AI infrastructure projects.
• Collaborative international environment with talented engineering teams.
• Opportunity to solve challenging technical problems at large scale.
• Culture focused on innovation, trust, and meaningful impact.
• Possibility to contribute to the future of cloud infrastructure and AI technology.