> Markdown version of [/jobs/ext/4601694-staff-software-engineer-compute](https://www.wearedevelopers.com/jobs/ext/4601694-staff-software-engineer-compute). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer - Compute

- **Company:** Lambda Labs
- **Location:** San Jose, CA, United States (Remote available)
- **Salary:** $314,000.0
- **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, Python (Programming Language), Kernel-Based Virtual Machine, Virtualization Technology, Rust (Programming Language), Programming Languages
- **Published:** November 6, 2026
- **Apply:** https://www.juju.com/job/7_4897166A6844361443ADF7A485EE83FD

## About the Role

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 HaveKnowledge 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

## Description

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 modelProvide 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.Who You are10+ years of, experience working on compute control plane distributed systems used for