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 InformationThe 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.
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
