HPC Systems Validation Lead - Cloud AI Infrastructure

Lambda Inc.; San Jose (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Cash & equity compensation

Health, dental & vision coverage for您

Job summary

Lambda Inc. in San Jose is seeking an experienced Hardware Engineer to lead system integration validation across HPC/AI platforms, from NPI to deployment. You will drive functional, stress and reliability testing, coordinate across fleet, infrastructure, and PMO teams, and own lab setups for repeatable hardware evaluation.

The role requires deep expertise in hardware validation, performance benchmarking, and vendor engagement to ensure production-ready platforms for AI workloads.

Qualifications

• 5+ years in hardware integration validation or related fields.
• Experience with HPC, data centre, or cloud infra hardware.
• Proficient in system integration testing and benchmarking at high levels.

Responsibilities

• Own system integration validation for HPC/AI hardware during NPI and deployment.
• Develop and execute functional, stress, reliability tests; enable scale testing.
• Collaborate across teams to enable automation and large-scale benchmarking.
• Manage firmware/software compatibility during NPI and post-production.
• Support root-cause analysis and improve product reliability.
• Set up lab/test infrastructure for repeatable hardware evaluation.
• Engage with vendors for hardware validation and manufacturing testing.
• Drive validation plans for key components (memory, SSDs, NICs, PSUs, etc).

Skills

Hardware integration

Fleet reliability engineering

Performance benchmarking

NPI cycles

Vendor management

Lab/test automation

Root cause analysis

Education

Bachelor's degree in Electrical Engineering

Tools

BMC

BIOS configurations

NIC configurations

Job description

Lambda Inc. in San Jose is seeking an experienced Hardware Engineer to lead system integration validation across HPC/AI platforms, from NPI to deployment. You will drive functional, stress and reliability testing, coordinate across fleet, infrastructure, and PMO teams, and own lab setups for repeatable hardware evaluation.

The role requires deep expertise in hardware validation, performance benchmarking, and vendor engagement to ensure production-ready platforms for AI workloads.