- Job type
- Full-time
- Work mode
- Not listed
- Level
- Not listed
- Department
- Engineering
- Experience
- 3+ years experience
- Posted
- Sep 17, 2026
About the role
Role Impact
You'll build the systems that turn bare-metal GPU servers into reliable, production-ready compute. Own the machine lifecycle from discovery and provisioning through validation, upgrades, repair, and secure reuse, reducing manual work as our fleet grows.
Core Technical Responsibilities
- Build automated discovery, network boot, OS imaging, and configuration workflows for GPU servers
- Automate BIOS, BMC, NIC, GPU driver, and firmware configuration with staged rollouts and safe recovery paths
- Develop hardware inventory and lifecycle services that track machine identity, configuration, health, and readiness
- Create acceptance tests and burn-in workflows for GPUs, memory, storage, and interconnects before capacity enters production
- Integrate provisioning and health checks with SLURM, Kubernetes, and compute allocation systems
- Build observability, quarantine, repair, and re-provisioning workflows; partner with datacenter teams to resolve hardware failures
- Implement secure credential handling, tenant isolation, and data sanitization across the server lifecycle
Technical Requirements
Required Experience
- 3+ years of experience operating Linux servers or building bare-metal infrastructure automation in production
- Hands-on experience with PXE/iPXE, DHCP, image provisioning, and out-of-band management such as Redfish or IPMI
- Strong software engineering and debugging skills in Python, Go, or a comparable language, plus Bash
- Experience designing reliable automation that handles partial failures, retries, and configuration drift
- Ability to own operational incidents and collaborate across hardware, networking, and platform teams
Infrastructure Skills
- Linux boot, systemd, kernel and driver troubleshooting, and OS image management
- Infrastructure automation with tools such as Ansible and Terraform
- GPU server diagnostics, PCIe topology, BMC telemetry, and firmware compatibility
- Network fundamentals including addressing, VLANs, DNS, and management networks
- Metrics, logs, alerting, and auditable configuration management
Nice to Have
- Experience with large NVIDIA GPU fleets, DGX/HGX platforms, or heterogeneous server vendors
- Experience with MAAS, Ironic, Tinkerbell, or similar provisioning systems
- Kubernetes or SLURM node lifecycle integrations
- Hardware qualification, automated burn-in, and fleet health scoring
- Contributions to open-source infrastructure tooling
Growth Opportunity
You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.
We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.
Apply now and join us in our mission to democratize access to planetary scale computing.
Compensation
Cash compensation range of $150,000–$300,000 plus equity incentives.