Senior/Staff Kubernetes Infrastructure Engineer

📋 Job Overview

Application fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

🏢 About fal

You will build the high-performance compute environments we deliver to customers. These environments span bare-metal servers, virtual machines with GPU passthrough, Kubernetes and Slurm clusters, distributed storage, and high-speed networking.

You will work across the infrastructure stack — from Linux images and hardware provisioning to cluster networking, GPU performance, observability, and lifecycle automation. The goal is to make every customer environment performant, reliable, isolated, and repeatable.

🎯 The Role

Design, automate, validate, and deliver the complete lifecycle of customer compute environments — from provisioning through upgrades, recovery, and decommissioning

Use AI aggressively to automate and accelerate every aspect of infrastructure delivery and operations

Provision dedicated Kubernetes and Slurm clusters tailored to customer workloads

Build and maintain Linux images and automated OS-provisioning workflows

Operate the NVIDIA GPU stack: 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 sound infrastructure designs

✅ Key Responsibilities

• Design, automate, validate, and deliver the complete lifecycle of customer compute environments — from provisioning through upgrades, recovery, and decommissioning
• Use AI aggressively to automate and accelerate every aspect of infrastructure delivery and operations
• Provision dedicated Kubernetes and Slurm clusters tailored to customer workloads
• Build and maintain Linux images and automated OS-provisioning workflows
• Operate the NVIDIA GPU stack: 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 sound infrastructure designs

📌 Required Qualifications

• 5+ years of experience building and operating production Linux infrastructure
• Strong production experience with Kubernetes on bare metal (bootstrapping, upgrades, HA control planes, etcd, containerd, CNI, CSI, ingress, load-balancing, observability, security, troubleshooting)
• Experience with Linux virtualization: KVM/QEMU, libvirt, VFIO device passthrough
• Experience operating NVIDIA GPUs on Linux and Kubernetes (drivers, container runtimes, device plugins, GPU Operator, GPU telemetry)
• Strong networking fundamentals: TCP/IP, L2/L3, VLANs, routing, packet-level troubleshooting (tcpdump, Wireshark)
• Practical scripting experience
• Experience with configuration-management tools such as Ansible
• Ability to diagnose complex, cross-layer infrastructure issues
• Strong communication and ability to drive technical decisions across teams
• Track record of moving quickly, taking ownership, and continuously improving systems

⭐ Desirable Experience

• Production Slurm experience
• High-performance networking: NVLink/NVSwitch, InfiniBand, RoCEv2, GPUDirect RDMA, NCCL, IMEX
• Hugepages, NUMA, CPU pinning
• SR-IOV, DPDK
• Distributed storage: Ceph, Lustre, Weka
• KubeVirt, OpenStack
• IPsec, WireGuard, Tailscale
• VXLAN, BGP, ECMP
• Bare-metal management: BMC, IPMI, Redfish, PXE/iPXE, Kickstart, cloud-init
• Network automation: NetBox, Nautobot, Nornir
• AI training, inference, or distributed GPU workload infrastructure
• Python or Go proficiency

🎁 Benefits

Compensation: $180K – $250K • Offers Equity

🛂 Visa & Eligibility