Senior Staff Site Reliability Engineer (AI Infrastructure)

Join D-Matrix, a company at the forefront of AI infrastructure. As a Senior Staff Site Reliability Engineer, you will be responsible for the reliability, automation, and observability of our infrastructure layer. This hands-on role involves working with colocation facilities, on-premises GPU clusters, cloud environments, and platform services. You will own systems end-to-end, from provisioning to live incident response, and collaborate with hardware and software teams. This is an opportunity to shape the future of AI and work with world-leading engineers and researchers.

• Assurer la fiabilité et la disponibilité des infrastructures, y compris les serveurs en colocation, les clusters sur site et les environnements cloud.
• Diriger la planification de la capacité et la gestion du cycle de vie du matériel pour les domaines d'infrastructure.
• Contribuer à l'automatisation des processus d'approvisionnement, de déploiement et d'exploitation à l'aide de Terraform et/ou d'Ansible.

• Kubernetes operational experience: cluster troubleshooting, workload management, storage, and networking
• Strong Linux systems knowledge with hands-on colocation or on-premises server infrastructure — networking, storage, systemd, kernel parameters, performance diagnostics, physical hardware, rack networking, and bare-metal provisioning
• Production-quality Python and/or Bash scripting, paired with incident response experience: structured triage, RCA production, and follow-through on action items
• Experience with observability tooling — Prometheus/Grafana, DataDog, Splunk, or equivalent — including building dashboards and writing alert rules
• Bachelor's or Master's in Computer Science, Electrical Engineering, or a related field (or equivalent experience); 7+ years in SRE, infrastructure engineering, or systems administration
• Production IaC experience with Terraform and/or Ansible — writing and maintaining configurations, not just running existing playbooks
• Experience operating customer-facing infrastructure or platform services with external reliability expectations
• Cloud infrastructure operations across AWS, Azure, or GCP, including hybrid environments spanning cloud and on-prem
• Experience deploying and operating AI-driven infrastructure tools — AIOps platforms, intelligent alerting, anomaly detection, or LLM-assisted diagnostics — in production
• HPC job scheduler experience: Slurm, LSF, or equivalent
• Knowledge of high-speed interconnect fabrics: InfiniBand, RoCE, or NVLink
• Experience with large-scale infrastructure automation — host lifecycle management, fleet auto-healing, or AIOps-driven operations — building tooling that reduces manual intervention, not just running it