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1–2 jobs· newest first

AI Cluster Architect
Vultr · Remote, US
$200K–$220KRemote · Full-time · Senior
GPU Platform SME (AI Infrastructure Validation)
Lenovo · Morrisville, US
On-site · Full-time · Mid

+10K new in the last hour

AI Cluster Architect

Vultr · Posted Nov 11, 2026

Remote, United States
Remote
Full-time · Senior
$200K–$220K per year
7+ years

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Creating and refining large-scale GPU cluster architectures within strict power and infrastructure limits, focusing on power-aware design.

Compensation

$200,000 - $220,000

Responsibilities

Architect large-scale GPU clusters within fixed site power budgets that optimizes for maximum GPU density while reserving necessary headroom for compute services, storage, and networking.
Model and validate power consumption across the full cluster bill of materials (GPUs, CPUs, NICs, switches, fabric components, storage, and facility limits).
Evaluate tradeoffs across multiple fabric networking architectures (InfiniBand, RoCE, SpectrumX) as well as multi-plane, 2-tier/3-tier, and rail-optimized topologies.
Determine network scale limits based on switch radix, link speed, topology, and blocking requirements.
Gather, interpret, and maintain detailed SKU-level power and thermal specifications for GPUs, NICs, switches, DPUs, storage, and server platforms.

Skills

GPU cluster design HPC cluster design AI cluster design InfiniBand RoCE SpectrumX Power-aware design Cluster architecture PCIe NVLink NVSwitch ROCm

Benefits

100% company-paid insurance premiums for employee medical, dental and vision plans
401(k) plan that matches 100% up to 4% with immediate vesting
Professional Development Reimbursement of $2,500 each year
11 Holidays + Paid Time Off Accrual + Rollover Plan
Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year

See full job description

GPU Platform SME (AI Infrastructure Validation)

Lenovo · Posted Nov 9, 2026

Morrisville, North Carolina, United States
On-site
Full-time · Mid
6+ years

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Lead GPU platform validation, architecture strategy, and technical leadership for next-generation AI infrastructure platforms.

Responsibilities

Study and validate GPU platform architectures
Define and execute integrated validation strategies
Coordinate validation readiness and infrastructure planning
Lead validation activities across node, rack, and cluster levels
Perform failure analysis, debugging, and root cause investigations

Requirements

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Computer and Information Science, or related discipline
Nice to have: Advanced AI infrastructure platforms (NVIDIA HGX, DGX, GB200, GB300, NVL72)
Nice to have: Rack-scale AI systems
Nice to have: GPU clusters
Nice to have: High-speed Ethernet fabrics

Skills

BIOS/UEFI Baseboard Management Controllers (BMC)Operating systems CPU and memory subsystems Storage technologies

Networking technologies

Software applications

GPU interconnect

High-speed networking

System integration testing

Functional validation

Performance testing

Reliability testing

Failure analysis

Root cause investigation

Linux administration

Command-line diagnostics

Server troubleshooting

Shell scripting

See full job description