Distinguished Engineer, Production Engineering, Cluster Management

NVIDIA

Distinguished Engineer defining cluster operations and production standards for NVIDIA’s DGX Cloud GPU infrastructure. Leading architecture, automation, reliability, and cross-team execution at scale.

Posted 9/3/2026full-timeSanta Clara • California, Oregon • 🇺🇸 United StatesSeniorLead💰 $320,000 - $488,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in defining technical strategies for large-scale distributed systems and cloud platforms, with a focus on operational excellence, architectural direction, and automation. Proven ability to lead cross-organizational technical efforts and improve production readiness through effective collaboration and engineering standards.

Highest-signal resume keywords

Kubernetes-Based Production SystemsInfrastructure AutomationDistributed Systems OperationsSoftware Engineering in Python or GoTechnical Leadership in Production Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Distributed SystemsInfrastructure PlatformsProduction EnvironmentsOperational WorkflowsAPIsService InterfacesAutomation FrameworksLinuxNetworkingProduction Reliability

Soft Skills

Cross-Team CollaborationTechnical JudgmentProblem-Solving

Tools & Technologies

KubernetesCloud PlatformsAutomation Tools

Industry Keywords

Technical StrategyArchitectural DirectionOperational StandardsProduction ReadinessService Reliability

Tech Stack

Tools & technologies

CloudDistributed SystemsGoKubernetesLinuxPython

About the role

Key responsibilities & impact

Define the long-range technical strategy for operating DGX Cloud clusters consistently across local data centers, hyperscalers, and NeoCloud environments
Define architectural direction and operating standards for cluster lifecycle, runtime delivery, restoration, release readiness, and steady-state operability
Guide roadmaps and execution of cross-organizational investments improving production readiness, operational safety, performance, and coordination
Make and influence high-impact technical decisions across platform, hardware, provider, and service teams
Build workflows, interfaces, and engineering handshakes across Kubernetes production service, provider and hardware preparation, on-prem, and bare-metal operations
Restructure operations and service-layer reliability domains
Build and evolve automation, APIs, operating workflows, and readiness gates for moving new capacity into stable production and balancing existing capacity
Implement production operating approaches that reduce manual input and increase ownership clarity, consistency, traceability, and release safety
Partner with platform, hardware, provider engineering, service owners, and Production Engineering leaders to convert recurring friction into durable improvements
Raise standards for operability, resilience, scalability, and performance through build leadership, architecture review, and technical standards

Requirements

What you’ll need

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
Track record of defining operating models, architectural direction, and engineering standards across multiple technical domains and organizations
Record leading large, cross-team technical efforts from concept through production, including aligning collaborators, navigating for clarity, and delivering measurable outcomes
Deep experience with 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 crafting operational workflows, APIs, service interfaces, or automation frameworks that become the standard way teams run production systems
Strong architectural judgment and a validated history of simplifying complex operational problems through reusable software, clear technical strategy, and durable engineering direction

Benefits

Comp & perks

Equity
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