Senior HPC Platform Hardware Engineer

Lambda•San Jose, CA

2d•$255,000 - $340,000•Hybrid

About The Position

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. Hardware Engineering at Lambda is responsible for building and scaling the physical infrastructure behind the Superintelligence Cloud. Our scope spans the full hardware lifecycle: roadmap and architecture, proof-of-concept for state-of-the-art platforms, new product introduction (NPI), and fleet-scale maintenance — all engineered for gigawatt-scale AI factories with rack-first design, advanced liquid cooling, and next-generation interconnects at the cutting edge of the industry. This position requires presence in our San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Requirements

5 years of technical lead experience on hardware NPI and deployment for HPC, data center, or cloud infrastructure products, familiar with hardware NPI processes.
Possess deep knowledge and hands-on experiences in one or many of the following hardware platforms: AI/ML, general compute (x86 and ARM), storage systems, or network switches.
Broad hardware engineering domain knowledge in one or many of the below areas: electrical, thermal, mechanical, power, signal integrity, safety, compliance, reliability and manufacturing.
Are comfortable working hands-on in labs to enable and bring up new hardware systems.
Experiences in identifying, triaging and root causing hardware issues during NPI and at scale in the fleet.
Experience in PLM systems and BOM structure.
Collaborate well cross functionally to deliver production-ready hardware solutions.
Strong ownership and can do attitude, self-starter who feels comfortable working in ambiguity.

Nice To Haves

10+ years of technical lead experience on hardware NPI and deployment for HPC, data center, or cloud infrastructure products, familiar with hardware NPI processes.
Experience supporting AI/ML infrastructure and accelerated compute hardware (e.g., NVIDIA, AMD, Intel).
Experience in rack scale server development and liquid cooling designs.
Exposure to fleet observability, BMC/BIOS/Network configuration and automation.
Background in performance tuning, benchmarking, and systems validation workflows.
Can interpret platform-level architecture requirements and select or adapt OEM and white-label solutions to fit.
Prior experience contributing to reference designs or large-scale infrastructure blueprints.
Are experienced with vendor-led product development cycles and can drive hardware evaluation, risk mitigation, and feedback into roadmap decisions.

Responsibilities

Serve as the hands-on technical lead for integrating OEM and white-label HPC AI/ML, general purpose compute, storage, and network hardware into Lambda’s HPC platform reference architectures.
Drive the end-to-end process of new product introduction (NPI) for hardware systems, including system bring-up, documentation, vendor technical engagement, production readiness, and closure of hardware risks.
Identify, debug, and resolve hardware issues across different hardware engineering domains during hardware NPI; support closure of critical fleet issues that require hardware design, vendor corrective action, or platform configuration changes.
Partner with HPC architects to translate platform blueprints into concrete hardware selections and system configurations.
Partner with the supply chain team on new vendor evaluation and QBR/HBR feedback on established vendors.
Own the hardware platform through NPI, working with PMO to de-risk execution, drive cross-functional closure of hardware readiness issues, and ensure platforms reach production on schedule.
Collaborate with the quality team and fleet reliability team during hardware NPI and after production to continuously improve product quality and reliability at scale.
Work cross-functionally with fleet engineering, deployment, operation and datacenter engineering teams to ensure on-time delivery and deployment, quality, compatibility, performance, and scalability of new systems.
Serve as the technical lead to evaluate, enable, and prototype new hardware in labs.
Review BOMs to ensure configuration accuracy, component compatibility, and alignment of key commodities and components to Lambda platform requirements.