Senior Technical Marketing Engineer – DSX AI Infrastructure Software

NVIDIA

Senior Technical Marketing Engineer showcasing NVIDIA DSX AI factory infrastructure software. Building validated deployments, technical content, demos, and training for AI infrastructure ecosystems.

Posted 8/26/2026full-timeSanta Clara • California • 🇺🇸 United StatesSenior💰 $160,000 - $322,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in deploying and operating multi-node GPU systems and Linux-based infrastructure, with a strong focus on automation, documentation, and collaboration across technical teams. Proficient in creating technical content and training materials to support AI factory operations and infrastructure management.

Highest-signal resume keywords

Multi-Node GPU Systems DeploymentKubernetes and Slurm ExpertiseInfrastructure-As-Code AutomationTechnical Documentation CreationLinux-Based Infrastructure Operations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure EngineeringSystems EngineeringSolutions ArchitectureSoftware EngineeringTechnical Marketing EngineeringSite Reliability EngineeringScriptingAPIsCI/CDGit-Based Workflows

Soft Skills

Excellent Communication SkillsProject ManagementCollaborationProblem-SolvingTechnical Recommendation Defense

Tools & Technologies

KubernetesSlurmHelmContainersGitOpsCloud InfrastructureHPCAI PlatformsTelemetryObservability

Industry Keywords

Data Center ManagementCloud ComputingAI InfrastructureMulti-TenancyOperational PracticesDeployment GuidesReference ArchitecturesTraining MaterialsTechnical ContentProduction Operations

Tech Stack

Tools & technologies

CloudKubernetesLinuxNode.jsPythonShell Scripting

About the role

Key responsibilities & impact

Stand up and validate complete DSX-aligned software stacks on multi-node GPU systems
Capture dependencies, configuration order, validation steps, and operational handoffs
Turn working deployments into technical content including reference architectures, quick-starts, installation and upgrade guides, troubleshooting runbooks, code examples, blogs, whitepapers, and demo videos
Build reusable examples and automation with APIs, Python or shell scripting, infrastructure-as-code, containers, Kubernetes, Slurm, Helm, GitOps, and CI/CD
Build demos, labs, and training for operating an AI factory, including deployment, tenant setup, upgrades, monitoring, scheduling, fault isolation, remediation, capacity management, and security
Demonstrate how data center hardware, infrastructure and cluster management software, orchestration, AI platforms, and workloads operate as one system
Test pre-release software using representative training and inference workloads
Identify interoperability and resiliency issues and provide feedback to Product and Engineering
Support solution architects, field teams, cloud and OEM partners, ISVs, and system integrators through repeatable assets, train-the-trainer sessions, live demos, and direct support
Collaborate with open-source and cloud-native communities on practical integration approaches, documentation, usability, and DSX software stack development
Use recurring customer, partner, field, and developer problems to set content priorities and recommend product improvements
Present work in customer briefings, partner workshops, industry events, webinars, and internal training

Requirements

What you’ll need

BS or MS in Computer Science, Computer Engineering, Electrical Engineering, another technical field, or equivalent experience
8+ years of experience in infrastructure engineering, systems engineering, solutions architecture, software engineering, technical marketing engineering, site reliability engineering, or a related role
Hands-on experience deploying and operating Linux-based data center, cloud, HPC, or AI infrastructure, including multi-node GPU systems and production operational practices
Strong working knowledge of Kubernetes and/or Slurm, including containers, operators, Helm charts, cluster lifecycle, and workload scheduling
Experience in several core infrastructure domains, including bare-metal provisioning, firmware and drivers, compute, Ethernet or InfiniBand networking, storage, identity, multi-tenancy, secrets or certificate management, telemetry, observability, and fleet health
Ability to automate deployments and operations through scripting, APIs, configuration management, infrastructure-as-code, Git-based workflows, and CI/CD
Examples of technical work for practitioner audiences, such as deployment guides, documentation, reference architectures, code repositories, demos, workshops, blog posts, conference talks, or training
Excellent written, verbal, and visual communication skills
Ability to explain a complex system and defend a technical recommendation to business and technical partners
Ability to balance multiple projects and constituents, prioritize under tight deadlines, and work well across Engineering, Product, Field, Marketing, and partner teams
Some travel will be required

Benefits

Comp & perks

Highly competitive salary
Comprehensive benefits package
Equity