{"schemaVersion":"jobsearcher.job.v1","id":"a6e3d37be9b44b95247d7b8a","url":"https://jobsearcher.com/jobs/a6e3d37be9b44b95247d7b8a","canonicalUrl":"https://jobsearcher.com/jobs/a6e3d37be9b44b95247d7b8a","title":"Senior Software Engineer - Fleet Engineering","description":"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.\n\nIf you'd like to build the world's best AI cloud, join us.\n\n*Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.\n\nFleet Engineering at Lambda is responsible for logically deploying, provisioning, and maintaining our rapidly growing fleet, spanning GPU, CPU, and storage hosts along with the InfiniBand and networking fabric that ties them together.\n\nAs a Senior Software Engineer in Fleet Engineering, you will build and improve the systems that take our clusters from hardware receiving through provisioning, configuration, and day-to-day operation in production. You will work on automation and tooling that keep the fleet consistent, healthy, and easy to operate as it grows. The systems you build directly determine how quickly and reliably new hardware turns into usable customer capacity.\n\nWhat You’ll Do\n\nFleet Engineering spans several teams. Depending on the team you join, your day-to-day will involve some combination of the following:\n\nDevelop and Maintain Production Systems: Design, implement, and improve the software that powers fleet lifecycle management, machine configuration, and cluster state at scale.\n\nAutomate Provisioning and Deployment: Build and enhance automation that takes clusters from logical design and racking through OS provisioning, configuration, validation, and customer hand-off.\n\nSupport New Hardware and Site Bring-Up: Enable bring-up, validation, and production readiness for new server, accelerator, and network platforms, as well as new datacenter sites.\n\nImprove Machine Lifecycle Workflows: Refine bare metal provisioning, firmware and DPU updates, imaging, and system health monitoring across the fleet.\n\nKeep Fleet State Consistent and Healthy: Build systems that reconcile intended against actual configuration, catch drift before it causes deployment failures, and maintain production SLAs.\n\nDebug Hardware and Firmware Issues: Investigate failures across BIOS, BMC, firmware, DPUs, networking, storage, and boot flows.\n\nCollaborate Across Teams: Work closely with datacenter and deployment operations, networking, architecture, security, and product engineering teams to build scalable, maintainable solutions.\n\nYou\n\nHave 5+ years of engineering experience\n\nAre fluent in Python, Go, or similar, and comfortable with APIs, distributed systems, and automation pipelines\n\nWork confidently in Linux environments and can debug across the OS, hardware, and networking layers\n\nAre excited about working at the intersection of hardware, software, and physical datacenter builds\n\nHave owned production systems with real SLAs\n\nCan lead technical design on medium-to-large features: take an ambiguous problem, write the doc, drive alignment across teams, and ship\n\nLeave systems, and the teammates around you, better than you found them\n\nNice to Have\n\nExperience in AI or ML infrastructure, or other hyperscale compute environments\n\nHands-on experience with bare metal provisioning and lifecycle management, including technologies such as PXE, Redfish, IPMI, BMC, DHCP, and DNS\n\nFamiliarity with datacenter physical infrastructure, including racks, switches, InfiniBand fabric, and power domains\n\nExperience diagnosing issues involving drivers, firmware, and hardware compatibility across GPU servers\n\nExperience with DPUs or programmable network accelerators\n\nExperience with network source-of-truth systems (NetBox or similar) or DCIM tooling\n\nExperience building Linux distributions or managing OS customization and imaging\n\nFamiliarity with Ansible or similar configuration management tooling\n\nExposure to Kubernetes and container orchestration concepts\n\nExperience incorporating AI-assisted development tools into engineering workflows, including code generation, debugging, test development, and documentation\n\nIf you don’t meet all of these requirements but believe you may be a good fit, please still apply and provide a cover letter that helps us understand your experience and readiness for this role.\n\nSalary Range Information\n\nThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.\n\nAbout Lambda\n\nFounded in 2012, with 500+ employees, and growing fast\n\nOur investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove\n\nWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG\n\nOur values are publicly available: https://lambda.ai/careers\n\nWe offer generous cash & equity compensation\n\nHealth, dental, and vision coverage for you and your dependents\n\nWellness and commuter stipends for select roles\n\n401k Plan with 2% company match (USA employees)\n\nFlexible paid time off plan that we all actually use\n\nEqual Opportunity Employer\n\nLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.\n\nCompensation Range: $230K - $395K","company":"Lambda","rawCompany":"lambda","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-19T16:19:26.479Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1244.00","title":"Network and Computer Systems Administrators","slug":"network-and-computer-systems-administrators"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Software Engineer - Fleet Engineering","description":"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.\n\nIf you'd like to build the world's best AI cloud, join us.\n\n*Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.\n\nFleet Engineering at Lambda is responsible for logically deploying, provisioning, and maintaining our rapidly growing fleet, spanning GPU, CPU, and storage hosts along with the InfiniBand and networking fabric that ties them together.\n\nAs a Senior Software Engineer in Fleet Engineering, you will build and improve the systems that take our clusters from hardware receiving through provisioning, configuration, and day-to-day operation in production. You will work on automation and tooling that keep the fleet consistent, healthy, and easy to operate as it grows. The systems you build directly determine how quickly and reliably new hardware turns into usable customer capacity.\n\nWhat You’ll Do\n\nFleet Engineering spans several teams. Depending on the team you join, your day-to-day will involve some combination of the following:\n\nDevelop and Maintain Production Systems: Design, implement, and improve the software that powers fleet lifecycle management, machine configuration, and cluster state at scale.\n\nAutomate Provisioning and Deployment: Build and enhance automation that takes clusters from logical design and racking through OS provisioning, configuration, validation, and customer hand-off.\n\nSupport New Hardware and Site Bring-Up: Enable bring-up, validation, and production readiness for new server, accelerator, and network platforms, as well as new datacenter sites.\n\nImprove Machine Lifecycle Workflows: Refine bare metal provisioning, firmware and DPU updates, imaging, and system health monitoring across the fleet.\n\nKeep Fleet State Consistent and Healthy: Build systems that reconcile intended against actual configuration, catch drift before it causes deployment failures, and maintain production SLAs.\n\nDebug Hardware and Firmware Issues: Investigate failures across BIOS, BMC, firmware, DPUs, networking, storage, and boot flows.\n\nCollaborate Across Teams: Work closely with datacenter and deployment operations, networking, architecture, security, and product engineering teams to build scalable, maintainable solutions.\n\nYou\n\nHave 5+ years of engineering experience\n\nAre fluent in Python, Go, or similar, and comfortable with APIs, distributed systems, and automation pipelines\n\nWork confidently in Linux environments and can debug across the OS, hardware, and networking layers\n\nAre excited about working at the intersection of hardware, software, and physical datacenter builds\n\nHave owned production systems with real SLAs\n\nCan lead technical design on medium-to-large features: take an ambiguous problem, write the doc, drive alignment across teams, and ship\n\nLeave systems, and the teammates around you, better than you found them\n\nNice to Have\n\nExperience in AI or ML infrastructure, or other hyperscale compute environments\n\nHands-on experience with bare metal provisioning and lifecycle management, including technologies such as PXE, Redfish, IPMI, BMC, DHCP, and DNS\n\nFamiliarity with datacenter physical infrastructure, including racks, switches, InfiniBand fabric, and power domains\n\nExperience diagnosing issues involving drivers, firmware, and hardware compatibility across GPU servers\n\nExperience with DPUs or programmable network accelerators\n\nExperience with network source-of-truth systems (NetBox or similar) or DCIM tooling\n\nExperience building Linux distributions or managing OS customization and imaging\n\nFamiliarity with Ansible or similar configuration management tooling\n\nExposure to Kubernetes and container orchestration concepts\n\nExperience incorporating AI-assisted development tools into engineering workflows, including code generation, debugging, test development, and documentation\n\nIf you don’t meet all of these requirements but believe you may be a good fit, please still apply and provide a cover letter that helps us understand your experience and readiness for this role.\n\nSalary Range Information\n\nThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.\n\nAbout Lambda\n\nFounded in 2012, with 500+ employees, and growing fast\n\nOur investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove\n\nWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG\n\nOur values are publicly available: https://lambda.ai/careers\n\nWe offer generous cash & equity compensation\n\nHealth, dental, and vision coverage for you and your dependents\n\nWellness and commuter stipends for select roles\n\n401k Plan with 2% company match (USA employees)\n\nFlexible paid time off plan that we all actually use\n\nEqual Opportunity Employer\n\nLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.\n\nCompensation Range: $230K - $395K","datePosted":"2026-08-19T16:19:26.479Z","dateModified":"2026-08-19T16:19:26.479Z","hiringOrganization":{"@type":"Organization","name":"Lambda","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a6e3d37be9b44b95247d7b8a"},"url":"https://jobsearcher.com/jobs/a6e3d37be9b44b95247d7b8a"}}