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, or Bellevue 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 website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.
What you'll do
Operate and maintain bare-metal Kubernetes clusters, scaling up to thousands of nodes
Handle cluster degradation, recovery, resizing, and incident response using fleet management tools
Participate in a well-managed on-call rotation for critical incidents
Assist customers with Kubernetes questions, workload integration, storage, and authentication
Work closely with our HPC Ops and Datacenter Ops teams for low-level or cross-functional issues
Use Python and Golang to create tooling and automate the validation of platform quality.
Design, build, and maintain scalable control plane services, operators, and custom controllers for Kubernetes
Develop automation for cluster lifecycle management: provisioning, upgrades, patching, and deletion.
Define and implement SLOs and SLIs for Kubernetes services, workloads, and platform reliability.
You
6+ years of experience in a SRE, operations engineer, or similar role, with a deep knowledge of running Linux clusters and systems
Strong programming skills in Go and Python; experience with GitOps (e.g., ArgoCD), Helm, and Kubernetes operators
Proven experience operating Kubernetes clusters in production environments (on-prem, EKS, GKE, or similar)
Can work either independently with limited direction or as part of a team
Can work with customers during incidents either via tickets, live messaging, or as part of a larger call.
Familiarity with observability tools like Prometheus, Grafana, FluentBit, and CI/CD pipelines
Proven experience provisioning Kubernetes using tools such as kubeadm, Cluster API, or similar
Nice to have
Deep Kubernetes expertise: CRDs, CSI, CNI, Kubernetes Operator Coding experience
Exposure to HPC clusters, AI/ML workloads, or large-scale GPU clusters
Hybrid or multi-cloud Kubernetes environment experience
Contributions to CNCF projects or Kubernetes SIGs
Why Join Us
Work on cutting-edge Managed Kubernetes platforms for AI/ML workloads
Influence the platform roadmap and help shape operations and reliability best practices
Collaborate with a highly skilled engineer
Opportunity to mentor and grow within a fast-growing, technology-driven environment
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 and your dependents
Wellness and commuter stipends for select roles
401k Plan with 2% company match (USA employees)
Flexible paid time off plan that we all actually use
Equal Opportunity Employer
Lambda 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.