EngineeringHybrid

Senior Platform Engineer - Core Infrastructure

Lambda · Hybrid

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Last seen by MeritLog September 8, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Lambda's Ashby job board and last checked it on September 8, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: Hybrid
Salary: $230K - $340K
Location: San Francisco Office (Fremont St)
Occupation: Computer Systems Engineers/Architects(O*NET 15-1299.08)
Company website: lambda.ai

Hiring context

How this role compares at Lambda

Lambda has 86 live roles in MeritLog’s catalog across 10 job families, and 30 of them are in engineering. 83 of those listings publish a pay range, a disclosure rate of 97%.

This role's posted range of $230K - $340K sits above 51% of the 79 other Lambda roles quoted over the same currency and period.

Lambda concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

Architect, deploy, and operate Kubernetes clusters across Lambda's bare-metal datacenters.
Build and maintain automation for cluster lifecycle management: provisioning, upgrades, and scaling.
Similar to SRE-level coding abilities (small scripts, k8s operators/CRDs a plus)
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.
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 junior engineers and raise the bar for platform engineering across the org.
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 Linux systems and understanding of system-level operations.
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.

What they're asking for

Experience with multi-cluster, multi-cloud, or hybrid environments.SkillPreferred
Knowledge of GPU scheduling, HPC workloads, or ML/AI infrastructure.SkillPreferred
Experience with workflow orchestration / durable execution frameworks (Temporal, Cadence, or Argo Workflows).SkillPreferred
Exposure to cost optimization and capacity planning for large clusters.SkillPreferred
Contributions to CNCF or Kubernetes open-source projects.SkillPreferred
CKA/CKS certification.CredentialPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job 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. 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 - Architect, deploy, and operate Kubernetes clusters across Lambda's bare-metal datacenters. - Build and maintain automation for cluster lifecycle management: provisioning, upgrades, and scaling. - Similar to SRE-level coding abilities (small scripts, k8s operators/CRDs a plus) - 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. - 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 junior 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 Linux systems and understanding of system-level operations. - 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.

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