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# Senior Technical Marketing Engineer - DSX AI Infrastructure Software

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $160,000.0 - $322,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Automation of Tests, Computer Engineering, Data Centers, Linux, Python (Programming Language), Node.Js, AI Infrastructure, Scripting, Kubernetes, Information Technology, Bare Metal, Slurm, Hardware Infrastructure
- **Published:** September 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pho4zlbfbj

## About the Role

* BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience.
 * 8+ years in infrastructure engineering, systems engineering, solutions architecture, or technical marketing engineering.
 * Hands-on experience with Linux-based data center and AI infrastructure, particularly multi-node GPU systems.
 * Proficient in Kubernetes and/or Slurm for cluster lifecycle and workload management.
 * Strong foundation in core infrastructure domains like bare-metal provisioning, networking, and observability.
 * Expertise in automation using scripting, APIs, and CI/CD processes.
 * Demonstrated ability to produce technical content for practitioner audiences.

## Description

This role will focus on validating and showcasing advanced AI infrastructure software across multi-node GPU systems in support of modern data center deployments. You will partner closely with product and engineering teams to turn complex technical capabilities into clear deployment guidance, training materials, and customer-facing content. The position blends hands-on systems validation, technical storytelling, and cross-functional enablement to help solution architects, partners, and practitioner audiences adopt scalable AI infrastructure more effectively., * Validate complete software stacks on multi-node GPU systems and document configurations and procedures.

 * Create technical content including deployment guides, troubleshooting runbooks, and demo videos.
 * Develop automation scripts and tools using APIs, Python, and infrastructure-as-code methodologies.
 * Design labs and training programs covering operational aspects of an AI factory.
 * Illustrate the interconnectivity of data center hardware, software, and workloads.
 * Test pre-release software with real-world workloads and provide actionable feedback to Product and Engineering teams.
 * Support solution architects and partners through training, demos, and repeatable technical resources.


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