Job Summary:
Lambda is a leader in AI cloud infrastructure serving tens of thousands of customers. They are seeking a Senior Software Engineer to develop and maintain production systems, automate infrastructure, and support new hardware introductions.
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.
• Support DPU Lifecycle Automation: Help provision, configure, update, and debug DPUs and programmable network accelerators.
• 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.
Qualifications:
Required:
• Have 6+ years of experience working with Go (Golang) or Python in production environments.
• Have 6+ years of experience with bare metal hardware management and configuration.
• Are 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.
Preferred:
• 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 with DPUs, NVIDIA BlueField, SuperNICs, or other programmable network accelerators.
• 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.
• Exposure to DPU-adjacent networking, storage, or security technologies such as OVS/OVN, BGP/FRR, SR-IOV/VFs, DOCA, NVMe emulation, telemetry agents, or certificate-based service authentication.
• Exposure to Kubernetes and container orchestration concepts.
Company:
Lambda is a cloud-based platform that provides high-performance GPU hardware and cloud infrastructure for AI model training and inference. Founded in 2012, the company is headquartered in San Jose, USA, with a team of 501-1000 employees. The company is currently Late Stage.