Senior Platform Engineer at Lambda

San Francisco, California, United States

Apply Now

$240,000 – $401,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud ComputingIndustries

Requirements

5+ years of experience in Platform, Infrastructure, or SRE roles
Expert knowledge of Kubernetes internals and operational practices
Proven experience running Kubernetes clusters in production at scale
Strong skills with Helm, Kustomize, or similar deployment tooling
Solid understanding of networking, service meshes, and container runtimes
Proficiency in infrastructure-as-code (Terraform, Pulumi, etc.)
Experience with observability stacks (Prometheus, Grafana, ELK, OpenTelemetry)
Familiarity with security best practices (network policies, secrets management, image scanning)
Strong coding skills in Go, Python, or similar for automation
Comfort with GitOps workflows and CI/CD integration
Excellent problem-solving skills and ability to operate in complex environments

Responsibilities

Architect, deploy, and manage Kubernetes clusters across AWS, OCI, and on-prem datacenters
Build and maintain automation for cluster lifecycle management, upgrades, and scaling
Own the reliability, performance, and security of Kubernetes workloads
Implement observability, logging, and alerting for clusters and critical workloads
Partner with developers to design scalable, cloud-native services and CI/CD pipelines
Define and enforce best practices for resource usage, networking, and RBAC
Lead incident response, root cause analysis, and post-mortems for cluster-related issues
Mentor junior engineers and contribute to internal platform engineering standards

Skills

Key technologies and capabilities for this role

KubernetesAWSOCIHelmKustomizeTerraformPulumiNetworkingService MeshesContainer RuntimesCI/CDObservabilityLoggingAlertingInfrastructure as CodeRBAC

Questions & Answers

Common questions about this position

What is the salary range for the Senior Platform Engineer position?

The salary range is $240K - $401K, though a higher or lower salary may be appropriate based on qualifications differing from those listed.

Is this a remote or hybrid role, and what are the office requirements?

This is a hybrid role requiring presence in the San Francisco, San Jose, or Seattle office 4 days per week, with Tuesday designated as the work-from-home day.

What key skills and experience are required for this Senior Platform Engineer role?

Requirements include 5+ years in Platform, Infrastructure, or SRE roles; expert Kubernetes knowledge; proven production-scale cluster experience; skills in Helm/Kustomize, networking/service meshes, IaC like Terraform/Pulumi, observability stacks, security practices, coding in Go/Python, GitOps/CI/CD, and strong problem-solving.

What is the company culture like at Lambda?

Lambda focuses on building world-changing AI deployments with people who love action and hard problems, emphasizing fast-paced work on massive-scale infrastructure for top AI labs.

What makes a strong candidate for this Senior Platform Engineer position?

A strong candidate has 5+ years in Platform/SRE roles with expert Kubernetes experience at production scale, plus skills in automation, observability, security, IaC, and coding; nice-to-haves like multi-cloud experience, GPU/ML knowledge, or open-source contributions strengthen applications.

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

Land your dream remote job 3x faster with AI

Try Jobo Free