Software Engineer - Fleet

Lambda•San Francisco, CA

2d•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. One person, one GPU. If you'd like to build the world's best AI cloud, join us. This position requires presence in our San Francisco/San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda cloud console, APIs, and systems, as well as internal tooling for system deployment, management, and maintenance.

Requirements

2+ years of experience working with Go (Golang) or Python in production environments.
2+ years of experience with configuration management tools and practices.
Comfortable working in Linux environments and debugging issues at the OS, hardware, and networking layers.
Can independently troubleshoot complex systems and communicate effectively across software, infrastructure, and vendor teams.

Nice To Haves

Experience with Go in infrastructure, systems, or backend development.
Hands-on experience with bare metal provisioning and lifecycle management, including technologies such as Redfish, BMC, IPMI, DHCP, and PXE.
Experience diagnosing issues involving drivers, firmware, and hardware compatibility across GPU servers.
Experience incorporating AI-assisted development tools into engineering workflows, including code generation, debugging, test development, and documentation.
Experience building Linux distributions or managing OS customization and imaging.
Familiarity with Ansible for system configuration and automation.
Exposure to Kubernetes and container orchestration concepts.

Responsibilities

Develop and Maintain Production Systems: Design, implement, and improve software that powers GPU fleet lifecycle management and machine configuration at scale.
Automate Infrastructure: Build and enhance automation frameworks for machine provisioning, configuration management, and deployment.
Support New Hardware Introduction (NPI): Enable bring-up, validation, and production readiness for new server and accelerator platforms.
Enhance Machine Lifecycle Processes: Improve and refine workflows for bare metal provisioning, firmware updates, and system health monitoring.
Debug Hardware and Firmware Issues: Investigate failures across BIOS, BMC, firmware, networking, storage, and boot flows.
Collaborate Across Teams: Work closely with infrastructure, security, and product engineering teams to develop scalable and maintainable solutions.