Senior Site Reliability Engineer (Sre, Compute Node Team)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Site Reliability Engineer (SRE, Compute Node Team) based in Spain.This role focuses on ensuring the reliability, scalability, and performance of advanced cloud infrastructure supporting AI-driven workloads.You will work at the intersection of Linux systems engineering, virtualization, and large-scale compute operations.The position offers the opportunity to design and improve foundational infrastructure used by developers and enterprises worldwide.You will take ownership of critical reliability challenges, from system debugging and observability to incident response and platform optimization.Working alongside experienced infrastructure and engineering teams, you will help shape the future of AI cloud platforms.This is an opportunity for a senior engineer who enjoys solving complex technical problems and building highly reliable systems at scale.AccountabilitiesThe 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.RequirementsThe 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.BenefitsCompetitive 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.#J-*****-Ljbffr

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.

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. #J-*****-Ljbffr