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Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Infrastructure Engineer based in Canada.

As a Senior Infrastructure Engineer, you will take ownership of business-critical infrastructure supporting demanding AI and GPU workloads.

You will design, deploy, and operate large-scale OpenStack and Kubernetes environments with a strong focus on performance, reliability, and scalability.

The role combines hands-on systems engineering with automation, infrastructure-as-code, observability, security, and incident response.

You will work directly with physical servers, racks, networking, storage, and GPU infrastructure across data-centre environments.

Your work will have a visible impact on platform stability, customer experience, and the ability to scale globally.

You will collaborate closely with platform, DevOps, AI, product, and support teams in a fast-moving, technically ambitious environment.

This is an ownership-driven opportunity for an engineer who enjoys solving complex infrastructure problems and improving systems end-to-end.

Accountabilities:

    • Design, deploy, operate, and continuously improve OpenStack and Kubernetes environments supporting high-performance GPU workloads.
    • Take end-to-end ownership of infrastructure performance, scalability, resilience, and operational reliability.
    • Build and maintain infrastructure using infrastructure-as-code, GitOps, CI/CD, and Git-based operational practices.
    • Automate provisioning, deployment, configuration, and recurring infrastructure workflows to improve efficiency and consistency.
    • Optimize GPU workload scheduling using Kubernetes and NVIDIA technologies to maximize platform performance and resource utilization.
    • Implement and improve monitoring, logging, alerting, and observability systems to identify and resolve infrastructure issues proactively.
    • Lead incident response activities, troubleshoot complex production problems, and drive post-incident improvements that strengthen overall reliability.
    • Maintain robust security controls across infrastructure and container environments, including RBAC, network policies, access controls, and tenant isolation.
    • Build, rack, cable, configure, and commission physical server and GPU infrastructure within data-centre environments.
    • Work with networking and storage systems to ensure reliable, scalable infrastructure for compute-intensive workloads.
    • Collaborate with Platform, DevOps, AI, Product, and Support teams to align infrastructure capabilities with technical and customer requirements.
    • Contribute to the continuous evolution of infrastructure architecture and operational practices as global environments scale.
    • Identify opportunities to improve automation, performance, reliability, and operational efficiency across the infrastructure platform.
    • Requirements

      • Extensive hands-on experience administering Linux systems, with strong technical depth across operating systems, troubleshooting, and infrastructure operations.
      • Proven experience physically building, assembling, cabling, configuring, and commissioning servers and racks.
      • Direct hands-on experience working in data centres, including physically installing and racking hardware on-site.
      • Willingness and ability to travel to data-centre sites in Quebec as required.
      • Strong understanding of networking and storage technologies and their role within large-scale infrastructure environments.
      • Experience installing, racking, and configuring GPU hardware is highly advantageous, particularly with NVIDIA platforms.
      • Production experience operating OpenStack and/or Kubernetes at scale is strongly preferred.
      • Experience with infrastructure automation, infrastructure-as-code, CI/CD pipelines, GitOps, and Git-based workflows is an advantage.
      • Exposure to high-performance computing, large-scale compute, or other demanding infrastructure environments is desirable.
      • Experience with Kubernetes GPU scheduling and NVIDIA tooling is a plus.
      • Strong troubleshooting and analytical abilities, with a methodical approach to diagnosing complex infrastructure issues.
      • Ability to take ownership of systems from design through deployment, operation, troubleshooting, and continuous improvement.
      • Comfortable working in a fast-paced environment where priorities can evolve and engineers are trusted to make decisions independently.
      • Strong collaboration and communication skills, with the ability to work effectively across technical and non-technical teams.
      • Contributions to open-source infrastructure or technology projects are a plus.
      • Benefits

        • Competitive salary.
        • Annual discretionary bonus scheme.
        • Employee wellbeing benefits.
        • 25 days of annual holiday plus public holidays.
        • Flexible working arrangements, with remote or hybrid options depending on role and location.
        • Significant autonomy and ownership, with the freedom to take initiative and experiment.
        • Opportunity to work on challenging, high-performance AI and GPU infrastructure.
        • Visible impact on infrastructure reliability, scalability, and customer experience.
        • Clear career progression and professional growth opportunities.
        • Collaborative international environment built around trust, transparency, and ownership.
        • Opportunity to contribute to the evolution of a rapidly scaling AI infrastructure platform and its engineering culture.
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