AMD

1 day ago

System Design Engineer  – AI Cluster Storage Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Shape AI and HPC storage infrastructure by creating reference architectures, configuration guides, and deployment blueprints. Build technical collateral—design docs, presentations, and “how it works” guides—to help internal teams, pre-sales engineers, and customers make informed hardware and software decisions. Perform deep evaluations of AI/HPC stacks with a storage focus, run reproducible benchmarking experiments, and develop reference implementations and tools to validate performance hypotheses.

Location: Austin, Santa Clara, Markham

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Create reference architectures, configuration guides, and deployment blueprints that help internal teams and customers make informed hardware and software decisions.
•Build a library of technical artifacts—including presentations, design documents, and “how it works” guides—to support pre-sales engineers and help others skill up from an HPC perspective.
•Perform deep technical evaluations of HPC and AI stacks focused on storage solutions, documenting how they work, where they fit, and the tradeoffs between storage technologies and vendors.
•Design and execute reproducible experiments and benchmarking harnesses to compare storage technologies for AI and HPC workloads.
•Develop small reference implementations and tools to validate performance hypotheses and analyze system behavior.

Key Requirements

•Hands-on experience with HPC clusters and HPC/AI-oriented storage solutions, including applying that expertise to AI/HPC infrastructure and storage solutions.
•Strong Linux fundamentals, including operating systems, networking, filesystems, containers, and performance tooling (perf, flamegraphs, nvprof/rocprof, basic eBPF).
•Familiarity with AI/HPC cluster orchestration and scheduling systems (e.g., Slurm, Kubernetes), plus MPI/OpenMP and distributed storage patterns or performance analysis.
•Experience with storage/data technologies such as parallel filesystems (Lustre, BeeGFS), object stores, RDMA, and data pipeline throughput and caching strategies.
•Ability to write evaluation docs/RFCs and create benchmarks with clear criteria, risks, and recommendations; communicate complex systems through structured documentation with diagrams and reproducible steps.

Experience:HPCAI

Education:Bachelor's in electrical, computer, or related engineering field

Skills:Systems thinkingDebuggingTradeoff decision-makingTroubleshootingSelf-directedProactiveClear communicationDocumentationExperimentationCollaboration

Languages:En-us

Tech Stack:HPCAILustreBeeGFSObject storesRDMASlurmKubernetesMPIOpenMPNCCLROCmRCCLInstinct GPUsEPYCTerraformAnsibleApptainerSingularityNAS

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

AMD

Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1969

Glassdoor: 3.9

Website LinkedIn

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AMD

1 day ago