Build and maintain production software for bare-metal GPU infrastructure across provisioning, hardware validation, firmware management, auditing, remediation, and production handoff. Integrate Redfish and vendor BMC interfaces, automate failure detection and recovery, debug issues spanning hardware, firmware, Linux, networking, and provisioning, and collaborate with vendors and infrastructure teams. The role also uses AI agents and LLM tools extensively for software development, testing, code review, and failure investigation.
NVIDIA DGX Cloud builds large-scale GPU infrastructure that powers the world’s most demanding AI workloads. Our Bare Metal Infrastructure team owns the software that turns newly racked hardware into reliable, validated production capacity. We’re looking for a software engineer with deep systems engineering instincts — someone who writes production code and understands how servers, firmware, BMCs, and networks actually behave. You’ll work across the full bare-metal lifecycle: new platform introduction, firmware qualification, automated provisioning, validation, remediation, and handoff to production. We use AI agents and LLM tools heavily in how we build software, and we want someone excited to push that further.
What you’ll be doing:
- Designing, building, and maintaining production services for bare-metal discovery, provisioning, hardware validation, firmware upgrades, auditing, and repair across large GPU fleets.
- Developing integrations with Redfish and vendor BMC interfaces to manage server state, collect inventory and health data, enforce configuration, and drive recovery — handling vendor differences in code.
- Contributing to and reviewing code in our Rust codebase, and building supporting tools and services in Go and Python.
- Turning recurring hardware, firmware, and connectivity failures into automated detection, validation, and repair workflows.
- Defining and implementing automated validation and handoff criteria for new platforms, firmware releases, and rack-scale deployments.
- Debugging complex failures across hardware, firmware, Linux, networking, and provisioning services, and feeding what you learn back into the software.
- Partnering with server and component vendors and with internal platform, networking, datacenter, and production engineering teams to resolve cross-boundary issues.
- Using AI agents and LLM tools daily to write, review, and test code and to investigate failures, and helping shape how the team builds with AI.
What we need to see:
- BS or MS in Computer Science, Computer Engineering, or equivalent experience.
- 5+ years building production infrastructure software, automation, or services, including substantial hands-on work with bare-metal server systems.
- Strong programming skills in Rust, Go, or Python, with a track record of designing, testing, shipping, and maintaining production code and willingness to work in Rust regularly.
- Deep knowledge of enterprise server hardware from multiple vendors (Dell, Supermicro, Lenovo, HPE), including BMCs, BIOS/UEFI, and firmware management.
- Direct experience with Redfish and IPMI for provisioning, health inspection, power management, or fault diagnosis, and with network boot (PXE/iPXE, DHCP, HTTP boot).
- Strong Linux knowledge: boot process, kernel and driver interactions, hardware discovery, and low-level failure analysis.
- Solid datacenter networking fundamentals with the ability to trace connectivity problems across host, management, and infrastructure networks.
- Demonstrated, regular use of AI agents and LLM tools in software development, with strong interest in improving and the judgment to validate what they produce.
Ways to stand out from the crowd:
- Production experience writing Rust.
- Experience with NVIDIA DGX or NVL72 systems, NVLink, InfiniBand, Spectrum-X, or BlueField DPUs.
- Background in hardware qualification, rack-scale bring-up, firmware certification, or new product introduction, including safe, scalable workflows for fleet firmware upgrades, configuration enforcement, hardware replacement, and recovery.
- Experience with Kubernetes, GitOps/Argo CD, or fleet-management platforms.
- Examples of AI-driven tooling or workflows you’ve built that measurably changed how you or your team ships software.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Similar Jobs
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