Member of Technical Staff - Bare Metal & Fleet Provisioning

Own Your Intelligence

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.

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.