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# Staff Software Engineer - AI Cloud Compute Platform

- **Company:** Lambda Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computing Platforms, BIOS, Booting (BIOS), C++ (Programming Language), Cloud Computing, Nvidia CUDA, Computer Networks, Data Centers, Device Drivers, Distributed Systems, Firmware, Hardware Design, InfiniBand, Python (Programming Language), Kernel-Based Virtual Machine, Linux Kernel, Quick EMUlator (QEMU), Cloud Services, Virtualization Technology, Rust (Programming Language), Extensible Firmware Interface, Kubernetes, Storage Technologies, Nvme, Golang, Programming Languages
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25197_16a00a9573b4a978e66cec7e74350d7f

## About the Role

* 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.
 * Basic knowledge of software defined networking fundamentals that informs secure, multi-tenant distributed systems.
 * Proven track record of leading large-scale semi-conductor hardware enablement and deployment initiatives.
 * Proven experience in deploying net-new data-centers into a global compute platform (not just working in existing data-centers).
 * Proficiency in one of more of the following programming languages: C/C++, Rust, Python, Go.

Nice to Have

 * Knowledge of Nvidia's AI Factory architectural components (including GPU hosts, CPU hosts, SuperNICs (ConnectX and Bluefield DPUs , and switches).
 * Knowledge of Nvidia's AI Factory software offerings (like DOCA, DOCA SNAP, CUDA, et al.)
 * Knowledge of Linux kernel internals, device drivers, and virtualization technologies (KVM, QEMU), kernel bypass technologies (like SR-IOV, DPDK, SPDK).
 * Experience with Cloud Service Provider Kubernetes offerings.
 * Knowledge of high-performance networking (InfiniBand, RoCE) and storage protocols (NVMe-oF).

## Description

*Note: This position requires presence in our Bellevue, San Francisco, or San Jose office location 4 days per week; Lambda's designated work from home day is currently Tuesday., As a Staff Software Engineer for the Compute pillar, you will play a critical role in defining the technical vision for Lambda's next-generation GPU and CPU host instance lifecycle and compute control plane. This role bridges the gap between high-level distributed systems and low-level semiconductor architecture to enable seamless, reliable cloud provisioning and lifecycle management of a heterogeneous compute platform at a massive scale. You will provide hands-on technical leadership that will guide development of a resilient compute control plane utilizing durable execution concepts and deep/unique hardware integration.

The position requires a deep understanding of the entire stack, from BIOS/firmware (UEFI), Linux kernel internals, modern DPU capabilities, distributed systems, cradle-to-grave system lifecycle management, to large-scale cloud-service provider (CSP) operations. You will drive high-impact, cross-functional initiatives, leading the work of multiple engineers to deliver enterprise-grade SLAs for the world's leading AI researchers., We are seeking an engineer with extensive experience in cloud infrastructure to build and optimize GPU-first compute systems. In this role, you will be responsible for:

 * 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, performance and reliability.
 * 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.