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 Seattle 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
Architect, deploy, and operate Kubernetes clusters across AWS and Lambda's bare-metal datacenters.
Build and maintain automation for cluster lifecycle management — provisioning, upgrades, and scaling.
Own the reliability, performance, and security of Kubernetes workloads in production.
Implement observability, logging, and alerting for clusters and critical workloads.
Partner with product teams to design scalable, cloud-native services and CI/CD pipelines.
Set the standards for resource management, networking, and RBAC across the platform.
Lead incident response, root-cause analysis, and post-mortems for platform issues.
Mentor engineers and raise the bar for platform engineering across the org.
You
5+ years in Platform, Infrastructure, or SRE roles, including running Kubernetes in production at scale.
Deep knowledge of Kubernetes internals and day-2 operations (upgrades, scaling, troubleshooting).
Strong with Helm, Kustomize, or similar, and GitOps-based delivery.
Proficient with infrastructure-as-code (Terraform, Pulumi, or equivalent).
Solid grounding in networking, service meshes, and container runtimes.
Hands-on with observability stacks (Prometheus, Grafana, OpenTelemetry).
Strong coding skills in Go or Python for automation and tooling.
Practical security experience: network policies, secrets management, and image scanning.
Nice to Have
Experience with multi-cluster, multi-cloud, or hybrid environments.
Knowledge of GPU scheduling, HPC workloads, or ML/AI infrastructure.
Experience with workflow orchestration / durable execution frameworks (Temporal, Cadence, or Argo Workflows).
Exposure to cost optimization and capacity planning for large clusters.
Contributions to CNCF or Kubernetes open-source projects.
CKA/CKS certification.
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.
Skills Required
- Work presence in San Francisco, San Jose, or Seattle office 4 days per week
- 5+ years in Platform, Infrastructure, or SRE roles, including running Kubernetes in production at scale
- Deep knowledge of Kubernetes internals and day-2 operations (upgrades, scaling, troubleshooting)
- Experience with Helm, Kustomize, or similar, and GitOps-based delivery
- Proficient with infrastructure-as-code (Terraform, Pulumi, or equivalent)
- Solid grounding in networking, service meshes, and container runtimes
- Hands-on with observability stacks (Prometheus, Grafana, OpenTelemetry)
- Strong coding skills in Go or Python for automation and tooling
- Practical security experience: network policies, secrets management, and image scanning
- Experience with multi-cluster, multi-cloud, or hybrid environments
- Knowledge of GPU scheduling, HPC workloads, or ML/AI infrastructure
- Experience with workflow orchestration / durable execution frameworks (Temporal, Cadence, or Argo Workflows)
- Exposure to cost optimization and capacity planning for large clusters
- Contributions to CNCF or Kubernetes open-source projects
- CKA/CKS certification
Lambda Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lambda and has not been reviewed or approved by Lambda.
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Fair & Transparent Compensation — Pay is considered competitive for an AI infrastructure company, with posted ranges and observed offers indicating strong packages for senior technical roles. Compensation is often characterized as competitive or top‑shelf, aligning with market expectations.
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Healthcare Strength — Health, dental, and vision coverage are characterized as strong, with broad‑network plans noted and positive experiences highlighted. This foundation supports overall satisfaction with core insurance benefits.
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Leave & Time Off Breadth — Flexible or unlimited PTO is described as actually used, complemented by paid holidays and sick time. Generous parental leave examples further expand the time‑off offering.
Lambda Insights
What We Do
Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.
