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Responsibilities Design, automate, validate, and deliver the complete lifecycle of customer compute environments from provisioning through upgrades, recovery, and decommissioning. Use AI to automate and accelerate infrastructure delivery and operations. Provision dedicated Kubernetes and Slurm clusters tailored to customer workloads. Build and maintain Linux images and automated operating-system provisioning workflows. Operate the NVIDIA GPU stack, including drivers, GPU Operator, NVIDIA Container Toolkit, device plugins, MIG, and GPU monitoring. Design Kubernetes and data-center networking using Cilium, Calico, MetalLB, VLAN, VXLAN, BGP, and ECMP. Configure distributed and shared storage for high-performance workloads. Build monitoring, alerting, diagnostics, and automated recovery for customer environments. Develop reusable tooling, standards, documentation, and runbooks. Collaborate with customers and internal teams to translate workload requirements into infrastructure designs. Requirements At least 5 years of experience building and operating production Linux infrastructure. Strong production experience with Kubernetes on bare metal, including bootstrapping, upgrades, highly available control planes, etcd, containerd, CNI, CSI, ingress, load balancing, observability, security, and troubleshooting. Experience with Linux virtualization using KVM/QEMU, libvirt, and VFIO device passthrough. Experience operating NVIDIA GPUs on Linux and Kubernetes, including drivers, container runtimes, device plugins, GPU Operator, and GPU telemetry. Strong networking fundamentals covering TCP/IP, Layer 2/Layer 3, VLANs, routing, and packet-level troubleshooting with tcpdump and Wireshark. Practical scripting experience and experience with configuration-management tools such as Ansible. Ability to diagnose complex cross-layer infrastructure issues and drive technical decisions across teams. Production Slurm experience is preferred. Preferred experience includes NVLink/NVSwitch, InfiniBand, RoCEv2, GPUDirect RDMA, NCCL, IMEX, hugepages, NUMA, CPU pinning, SR-IOV, and DPDK. Preferred distributed-storage experience includes Ceph, Lustre, or Weka. Preferred experience includes KubeVirt, OpenStack, IPsec, WireGuard, Tailscale, VXLAN, BGP, ECMP, BMC, IPMI, Redfish, PXE/iPXE, Kickstart, cloud-init, NetBox, Nautobot, and Nornir. AI training, inference, or distributed GPU workload infrastructure experience is preferred. Python or Go proficiency is preferred. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.