Fal2mo ago

Software Engineer, Infrastructure

San Francisco,San Franciscosenior

EngineeringOtherDevOps & InfrastructureSoftware EngineerInfrastructure EngineerSoftware EngineeringDevops EngineerInfrastructure & Cloud

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Quick Summary

Key Responsibilities

hardening baselines, SELinux/AppArmor policies, SSH key management, vulnerability scanning,

Requirements Summary

boot process, kernel tuning, networking, storage, systemd, cgroups, namespaces, performance profiling Strong experience with configuration management and infrastructure-as-code: Ansible, Terraform,

Technical Tools

EngineeringOtherDevOps & InfrastructureSoftware EngineerInfrastructure EngineerSoftware EngineeringDevops EngineerInfrastructure & Cloud

You are a hands-on engineer who builds the software and processes that keep a large fleet of GPU servers healthy and productive. You write systems and tooling for managing 1000s of servers including provisioning, health monitoring, error detection, and recovery — and when something breaks that automation can’t fix, you drive resolution with partners.

Responsibilities

~1 min read

→Build and maintain Python fleet tracking system that manages the full lifecycle of servers including contracting and procurement, target use, pricing, availability, health, RMAs, etc
→Build server management tooling that automates provisioning, health checks, GPU diagnostics, recovery and alerting
→Create and maintain metrics, dashboards, and alerting for hardware health across the fleet (GPU errors, disk failures, network issues, thermals)
→Leverage AI to an extreme level to build tools and automate alerting and recovery
→Implement and enforce OS-level security: hardening baselines, SELinux/AppArmor policies, SSH key management, vulnerability scanning, and compliance automation
→Manage and optimize distributed and local storage systems supporting model weights, checkpoints, and ephemeral scratch: NVMe arrays, NFS, parallel file systems, and object storage
→Tune Linux systems for AI workloads: kernel parameters, NUMA topology, CPU pinning, hugepages, I/O schedulers, and GPU driver stack optimization (NVIDIA drivers, CUDA, container runtimes)
→Develop a suite of automated error detection and recovery processes
→Work with partners to solve technical issues

Requirements

~1 min read

3+ years experience managing bare-metal and cloud based server fleets at scale (100+ nodes)
Strong software engineering skills in Python; you write production tooling, not scripts
Deep Linux systems knowledge: boot process, kernel tuning, networking, storage, systemd, cgroups, namespaces, performance profiling
Strong experience with configuration management and infrastructure-as-code: Ansible, Terraform, cloud-init
Solid understanding of storage technologies: LVM, RAID, NVMe, NFS, Lustre or GPFS, and Linux I/O stack tuning
Familiarity with hardware diagnostics and failure modes (GPUs, NVMe, NICs, memory)
Experience building internal tools or dashboards for infrastructure visibility
Excellent communication and ability to drive technical decisions across teams
Self-starter who executes quickly, takes ownership, and constantly seeks improvement

Nice to Have

~1 min read

Familiarity with network configuration and diagnostics (VLAN, VXLAN, ECMP, BGP, tcpdump)
Experience with NVIDIA GPU infrastructure: driver management, health monitoring, DCGM, NVLink/NVSwitch diagnostics, RDMA, InfiniBand/RoCEv2
Experience with AMD GPUs
Experience with bare metal and VM provisioning (PXE/iPXE, Kickstart, libvirt, Qemu/KVM)
Experience with compliance frameworks relevant to cloud providers (SOC 2, ISO 27001)