> Markdown version of [/jobs/ext/2266950-senior-technical-marketing-engineer-dsx-ai-infrastructure-software](https://www.wearedevelopers.com/jobs/ext/2266950-senior-technical-marketing-engineer-dsx-ai-infrastructure-software). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Technical Marketing Engineer - DSX AI Infrastructure Software - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $160,000.0 - $253,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Cloud Computing, Cloud Engineering, Computer Clusters, Configuration Management, Computer Engineering, Continuous Integration, Data Centers, Linux, Ethernet, Firmware, InfiniBand, Open Source Technology, Reliability Engineering, Software Engineering, AI Infrastructure, SSL Certificate Management, Software Repository, Scripting, High Performance Computing, Kubernetes Helm Charts, Git Flow, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Bare Metal, Slurm - **Published:** August 27, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Technical-Marketing-Engineer---DSX-AI-Infrastructure-Software_JR2024197 ## About the Role * BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or 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, such as 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. Links to example contributions are greatly appreciated. * Excellent written, verbal, and visual communication skills. You can explain a complex system and defend a technical recommendation to both 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. Ways to stand out from the crowd: * 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, networking, storage, scheduling, or hardware-health issues. * Experience with AI training and inference workloads and the requirements for operating them dependably on accelerated infrastructure. * Experience connecting infrastructure software to facilities or operational technology systems, including power, cooling, building management systems. * Active participation in cloud-native, HPC, infrastructure automation, or open-source communities, including published examples or project contributions. ## Description * Test pre-release software using representative training and inference workloads. Identify rough edges, assess interoperability and resiliency, and provide Product and Engineering with clear feedback before customers face similar issues. * Help solution architects, field teams, cloud and OEM partners, ISVs, and system integrators use the stack successfully through repeatable assets, train-the-trainer sessions, live demos, and direct support on important engagements. * Collaborate with open-source and cloud-native communities to demonstrate practical integration approaches, address documentation and usability shortcomings, and assist partners in expanding and developing the DSX software stack. * Listen for recurring problems from customers, partners, the field, and developers. Use those signals to set content priorities and recommend product improvements, then track whether the work reduces deployment time and improves operational success. * Present your work in customer briefings, partner workshops, industry events, webinars, and internal training. 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