Use Kubernetes and cloud-native primitives as an infrastructure fabric when appropriate. This includes controllers, operators, reconciliation loops, and open source components. These components can operate safely at rack and fleet scale. Build open source infrastructure software that can be embraced in different forms, including libraries, services, controllers, operators, and integration APIs for internal deployments and CSP environments.
Bridge hardware and software teams across firmware, BMC, BIOS, boot flows, OS images, drivers, networking, NVLink domains, InfiniBand, GPUs, DPUs, CPUs, and system management interfaces. Translate forward-looking infrastructure roadmaps into formal software requirements, architecture specifications, and execution plans that align teams across the organization.
Partner directly with hyperscalers, CSPs, enterprise customers, internal component leads, vendors, and business partners to align infrastructure capabilities with real-world deployment and integration needs. Establish reliability, security, validation, and left-shift strategies that reduce risk before hardware reaches production environments.
Mentor senior engineers and technical leads, raising the engineering bar for large-scale networked systems, foundational software, and rack-scale control plane development.
Make high-quality technical decisions in ambiguous environments, balancing customer needs, schedule, hardware realities, software maintainability, open source adoption, and long-term infrastructure evolution.
What We Need To See
BS or MS in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent experience. Proven experience (15+ years) in systems architecture, system software, distributed systems, infrastructure control planes, or infrastructure engineering.
Solid architectural knowledge of coordination frameworks, state machines, declarative APIs, reconciliation loops, lifecycle orchestration, failure handling, upgrade and rollback workflows, and distributed systems tradeoffs.
Practical coding skills in Go, C++, or Rust, encompassing the capability to write, review, and direct production-quality infrastructure software. Experience with Rust is highly valued.
Experience with Kubernetes or similar orchestration systems, especially as a fabric for managing infrastructure, hardware resources, or large-scale infrastructure services. Experience with Linux-based infrastructure software, OS rollout and image management, kernel or driver interactions, firmware lifecycle, and hardware bring-up workflows.
Strong understanding of data center networking technologies and protocols, such as Ethernet, InfiniBand, RDMA, and fabric-level manageability. Experience with complex accelerator-based systems, including GPUs, DPUs, FPGAs, custom silicon, or other high-performance computing systems.
Expertise in in-band and out-of-band management architectures, including BMCs, Redfish, IPMI, and related system management protocols. Ability to work with security experts to define practical tradeoffs across secure boot, attestation, access control, update safety, serviceability, and ease of operation.
Experience crafting software intended for open source release, including API stability, modularity, documentation, community usability, and clean separation between shared software and deployment-specific integrations.
Experience using AI-assisted development tools responsibly as an engineering multiplier for coding, test generation, debugging, build iteration, and documentation.
Established skill in specifying requirements, guiding architecture, and managing delivery across various engineering teams and organizations. Strong written and verbal communication skills, enabling clear explanation of complex hardware/software tradeoffs to engineering leaders, customers, partners, and executives.
Ways To Stand Out from the crowd
Built software supporting multiple adoption models — internal services, CSP-integrated offerings, reusable libraries, and customer-extensible APIs. Strong Rust skills in systems, infrastructure, or hardware-adjacent software.
Multiplied team impact through reference implementations, design reviews, shared libraries, architecture docs, dev workflows, and AI-assisted engineering. Hands-on with fleet-scale provisioning, updates, rollback, observability, health, and remediation.
Led across the full data center product lifecycle: inception, pre- and post-silicon, manufacturing, deployment, and operations. Familiar with open source ecosystems, contribution models, and balancing community collaboration with product needs.
Deep experience with rack- or cluster-scale systems spanning compute, networking, storage, accelerators, firmware, and infra management as one operational domain. Skilled at finding simple, durable abstractions in complex systems to align teams, customers, and long-term direction.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 21, 2026.
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.
