Senior Technical Marketing Engineer - DSX AI Infrastructure Software

NVIDIA DSX brings together facilities infrastructure, hardware, software, simulation, and partner technologies to build and run efficient AI factories. We are looking for a Senior Technical Marketing Engineer to show and educate our AI factory ecosystem how to bring up and operate the entire stack, ranging from facilities and multi-node GPU infrastructure to provisioning, networking, storage, cluster orchestration, security, observability, and workload enablement.

Responsibilities

• Stand up and validate complete DSX-aligned software stacks on multi-node GPU systems. Capture dependencies, configuration order, validation steps, and operational handoffs.
• Create technical content: reference architectures, quick-starts, installation guides, troubleshooting runbooks, code examples, blogs, whitepapers, and demo videos.
• Develop 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, and security.
• Collaborate with teams to demonstrate how data center hardware, infrastructure software, orchestration, AI platforms, and workloads operate as one system.
• Test pre-release software using representative workloads and provide feedback to Product and Engineering.
• Support solution architects, field teams, and partners in using the stack successfully.
• Collaborate with open-source and cloud-native communities to demonstrate integration approaches and address documentation shortcomings.
• Listen for recurring problems and use them to set content priorities and recommend product improvements.
• Present work in customer briefings, partner workshops, industry events, and internal training.

Requirements

• BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
• 8+ years of experience in infrastructure engineering, systems engineering, solutions architecture, software engineering, technical marketing 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.
• Strong working knowledge of Kubernetes and/or Slurm, including containers, operators, Helm charts, cluster lifecycle, and workload scheduling.
• Experience in core infrastructure domains, such as bare-metal provisioning, firmware, compute, networking, storage, identity, and telemetry.
• Ability to automate deployments and operations through scripting, APIs, and infrastructure-as-code.
• Excellent written, verbal, and visual communication skills.
• Ability to balance multiple projects and constituents, prioritize under tight deadlines, and work well across teams.

Nice to Have

• Experience with NVIDIA DSX, DGX systems, DGX Cloud, NVIDIA AI Enterprise, BlueField DPUs, DOCA, or related NVIDIA infrastructure software.
• Experience operating large GPU clusters and diagnosing distributed performance issues.
• Experience with AI training and inference workloads and their requirements on accelerated infrastructure.
• Active participation in cloud-native, HPC, infrastructure automation, or open-source communities.