Lambda is The Superintelligence Cloud that builds supercomputers for AI training and inference and provides AI-native infrastructure to researchers, enterprises, and hyperscalers.
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. *Note: 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. About the Role As a Senior Software Engineer on Lambda’s Core Cloud Platform team, you will build the control-plane systems that power Lambda’s GPU cloud. The team owns core platform capabilities across compute lifecycle, bare metal orchestration, maintenance actions, deployment readiness, reliability, and operational tooling. You will work on systems that turn physical GPU infrastructure into reliable, customer-facing cloud capacity: APIs, workflows, orchestration layers, schedulers, and operational surfaces for instance lifecycle, host reclaim, validation, maintenance, and safe regional deployments. This role is a strong fit for engineers who enjoy distributed systems, cloud infrastructure, operational excellence, and working close to the hardware/software boundary. What You’ll Do - Build and operate core cloud platform services for compute lifecycle, bare metal hosts, capacity, placement, and maintenance workflows. - Design reliable APIs, backend services, state machines, and orchestration systems that power Lambda’s GPU cloud. - Work on bare metal lifecycle systems including launch, terminate, restart/reboot, host reclaim, validation, quarantine, and return-to-pool workflows. - Improve deployment, observability, testing, alerting, runbooks, and operational readiness for business-critical control-plane services. - Debug complex production issues across distributed services, infrastructure dependencies, networking, and cloud workflows. - Partner with infrastructure, networking, fleet, security, support, and product teams to define cross-system contracts and deliver end-to-end cloud capabilities. - Contribute to architecture, design docs, code reviews, incident follow-through, and mentoring across the team. You May Be a Good Fit If You - Bachelor's degree or equivalent working experience. - Have 6+ years of professional software engineering experience building production backend or distributed systems. - Are strong in Python, Go, or a similar backend/system language. - Have experience designing and operating APIs, workflow engines, schedulers, orchestration services, or other distributed systems. - Understand reliability fundamentals: fault tolerance, idempotency, retries, state machines, failure handling, and production debugging. - Have experience with cloud or cloud-like infrastructure primitives such as compute, networking, storage, capacity management, identity, or fleet operations. - Are comfortable with Linux, containers, Kubernetes, infrastructure automation, and service deployment patterns. - Have owned production services, participated in on-call, and improved systems based on operational learnings. - Care about testability, CI/CD, observability, metrics, logging, alerting, and supportable operations. - Can take ambiguous infrastructure problems and drive them to clear designs, implementation plans, and production outcomes. - Communicate clearly across engineering, product, support, infrastructure teams, and leadership. Nice-to-Haves - Experience building cloud control planes, compute platforms, schedulers, or infrastructure orchestration systems. - Experience with bare metal, GPU infrastructure, HPC, Kubernetes, Slurm, or large-scale AI/ML infrastructure. - Experience with host lifecycle, provisioning, validation, firmware, BMC/Redfish, fleet management, or maintenance workflows. - Familiarity with Temporal, Airflow, event-driven systems, or durable workflow orchestration. - Networking experience with VPCs, firewalls, SDN, InfiniBand, routing, or distributed systems networking. - Security-minded engineering experience, including identity, authorization, audit logging, attestation, or tenant isolation. You Will Be Successful in This Role If You - Enjoy building foundational cloud systems where correctness, reliability, and operational clarity matter. - Are comfortable working across product, infrastructure, fleet, networking, security, and support boundaries. - Can break down ambiguous platform problems into concrete APIs, workflows, contracts, and implementation plans. - Care deeply about production behavior, not just code completion. - Move fast while maintaining high standards for reliability, testability, and supportability. - Communicate clearly and proactively, especially when risks, dependencies, or tradeoffs are unclear. - Want to help build the cloud platform layer for large-scale AI infrastructure. Salary Range Information The 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. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our 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 - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you