Distinguished Engineer, Production Engineering, Cluster Management

NVIDIA•Santa Clara, CA

10d•$320,000 - $488,750•Hybrid

About The Position

NVIDIA is seeking a Distinguished Engineer to serve as a senior technical leader in Production Engineering, focused on leading cluster activities within DGX Cloud GPU capacity. Production Engineering ensures large-scale production systems remain reliable, manageable, and increasingly automated across DGX Cloud resources by combining software engineering, systems engineering, and production expertise. The role defines the operational structure for DGX Cloud clusters across on-premises data centers, hyperscalers, and NVIDIA Cloud Partner environments. Its scope includes Kubernetes service management, provider and hardware readiness, on-premises infrastructure, deployment and operational preparedness, service-reliability collaboration, and the processes that integrate these areas into a unified production system. This is a hands-on technical leadership role responsible for defining architectural direction and technical strategy for cluster operations throughout DGX Cloud, establishing operating standards, guiding the evolution of production operations, and advancing cross-organizational capabilities. The successful candidate will contribute deeply to building and implementation while also leading through influence across teams and high-consequence production outcomes. The focus is ensuring the broader DGX Cloud cluster estate functions optimally in a live environment through strong technical leadership, consistent workflows, clear ownership, and effective cross-team coordination.

Requirements

BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field, or equivalent experience.
18+ years of experience building and operating large-scale distributed systems, infrastructure platforms, or production environments.
Company-level technical leadership at principal, distinguished, or equivalent scope in production engineering, SRE, infrastructure software, or cloud platforms.
A consistent track record defining operating models, architectural direction, and engineering standards across multiple technical domains and organizations.
A consistent record leading large, cross-team technical efforts from concept through production, aligning collaborators, navigating ambiguity, and delivering measurable outcomes.
Deep experience in one or more of Kubernetes-based production systems, infrastructure automation, or distributed systems operations.
Strong software engineering skills in Python, Go, or similar low-level programming languages.
Deep understanding of distributed systems, Linux, networking, containers, and production reliability concerns.
Experience developing operational workflows, APIs, service interfaces, or automation frameworks that become the standard way teams run production systems.
Strong architectural judgment and a demonstrated history of simplifying complex operational problems through reusable software, clear technical strategy, and durable engineering direction.

Nice To Haves

Defined the structural foundation for a large, heterogeneous infrastructure environment spanning multiple platforms or providers.
Established widely used operating standards, architectures, APIs, or workflows that improved reliability, operability, or performance at company scale.
Built automation and engineering interfaces connecting platform teams, infrastructure teams, and service owners into a consistent production system.
Experience improving production readiness, restoration, runtime safety, or release quality for large-scale infrastructure.
Comfort setting technical strategy, reviewing architecture at scale, writing code, and driving adoption across organizational boundaries.

Responsibilities

Define the long-range technical strategy for operating DGX Cloud clusters consistently across local data centers, hyperscalers, and NeoCloud environments.
Set architectural direction and fundamental operating standards for cluster lifecycle, runtime delivery, restoration, release readiness, and steady-state operability.
Guide the roadmap and execution of cross-organizational investments that improve production readiness, operational safety, performance, and coordination.
Make and influence high-impact technical decisions that shape how platform, hardware, provider, and service teams operate DGX Cloud resources in production.
Build durable workflows, interfaces, and engineering handshakes across Kubernetes production services, provider and hardware preparation, on-premises and bare-metal infrastructure, and service-layer reliability.
Build and evolve automation, APIs, operating workflows, and readiness gates to bring new capacity into stable production and keep existing capacity balanced.
Implement operating approaches that reduce manual effort, clarify ownership, and improve consistency, traceability, and release safety.
Partner with platform teams, hardware and provider engineering, service owners, and Production Engineering leaders to turn recurring friction into durable software, process, and operational-interface improvements.
Raise engineering standards for operability, resilience, scalability, and performance through technical leadership, architecture reviews, and technical standards.