Staff Software Engineer, Cloud Compute & GPU Lifecycle

Lambda; United States; Remote; USD 180,000 - 320,000; Full time

Job summary

Lambda, The Superintelligence Cloud, is seeking a Staff Software Engineer for the Compute pillar to define the technical vision of the next-generation GPU/CPU host lifecycle and compute control plane at scale.

You will mentor engineers, lead multi-team initiatives, and bridge BIOS/firmware, kernel, and cloud-service provisioning to deliver enterprise-grade SLAs for customers in a fast-growing AI cloud.

Qualifications

• 10+ years of experience working on compute control plane distributed systems used for deploying and lifecycle managing heterogeneous compute platforms into data-centers, built for resilience at scale.
• Deep expertise in durable execution models and distributed systems used in cloud-service provisioning.

Responsibilities

• Designing and implementing a highly available and reliable GPU and CPU host and instance lifecycle control plane.
• Guide technical decisions involving semiconductor architecture, BIOS/Firmware settings, system boot methodologies, and DPU utilization to optimize host capabilities.
• Guide design of compute platform multi-tenant security model.
• Provide technical leadership and mentorship for senior engineers across several teams to execute on complex infrastructure roadmaps and technical strategy.
• Collaborate with product and data center organizations to translate customer requirements into scalable infrastructure capabilities.
• Work with customers on translating vague customer technical requirements into concrete engineering deliverables.
• Set engineering standards and lead design reviews for mission-critical cloud software at scale.

Skills

Distributed systems

Cloud infrastructure

Technical leadership

Compute control plane

BIOS/firmware knowledge

Linux kernel internals

Job description

Lambda, The Superintelligence Cloud, is seeking a Staff Software Engineer for the Compute pillar to define the technical vision of the next-generation GPU/CPU host lifecycle and compute control plane at scale.

You will mentor engineers, lead multi-team initiatives, and bridge BIOS/firmware, kernel, and cloud-service provisioning to deliver enterprise-grade SLAs for customers in a fast-growing AI cloud.