Jobgether
Senior Site Reliability Engineer (SRE, Compute Node Team)
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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 United Kingdom.
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.
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.
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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.
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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.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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