Platform Support Architect

🕒 Yesterday

🏄 California – Remote

🏄 California – Remote

💵 $175k - $200k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📞 Support Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

DDN

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1998

🤖 Artificial Intelligence

💰 $10M Funding Round on 2011-06

Artificial Intelligence • Data Center and Cloud Computing • High Performance Computing

DDN is a global leader in AI data intelligence solutions, providing high-performance computing and sophisticated data management technologies. With a focus on accelerating AI deployments and advanced data analytics, DDN's products, including the Data Intelligence Platform and advanced storage systems, serve diverse sectors such as healthcare, financial services, and government. DDN is committed to transforming enterprise data infrastructure to leverage the full potential of AI and drive operational efficiency.

📋 Description

• Act as the primary NVIDIA AI Enterprise and vector database solutions expert for HyperPOD customer environments • Own complex end-to-end triage across GPU, NVAIE services, vector DB, Kubernetes, Docker, high-speed networking, and Infinia storage • Diagnose and resolve performance bottlenecks in RAG and agentic AI workflows • Collect and interpret logs and telemetry across Linux, containers, Kubernetes, GPU stack, vector DB, and storage/networking • Author and maintain support triage runbooks and checklists for HyperPOD • Define and validate unified diagnostics bundles • Collaborate with observability and tools teams to shape dashboards • Build hands-on labs and PoCs that mirror customer use cases • Develop reusable technical assets

🎯 Requirements

• 5+ years in Linux-based infrastructure roles (SRE, MLOps, platform engineering, or L2/L3 support) • Strong hands-on experience with containers and Kubernetes • Demonstrated experience operating GPU-accelerated workloads in production • Familiarity with DGX/HGX or similar GPU cluster platforms • Practical experience with AI storage and networking for HPC/AI clusters • Experience with one or more vector databases (Milvus, Qdrant, Pinecone, etc.) • Solid understanding of RAG and Generative AI workflows • Familiarity with NVIDIA AI Enterprise components and toolchain • Experience designing, operating, or supporting MLOps/GenAI pipelines • Strong diagnostic skills across Linux, containers, Kubernetes, GPUs, storage, and networking • Track record of building reusable technical assets that improve support readiness and partner/customer success • Excellent communication skills, capable of clearly explaining complex AI platform topics to both engineers and executive stakeholders.