Platform Engineer

Cube; San Francisco (CA); Remote; USD 150,000 - 190,000; Full time

Job summary

Cube is seeking a Platform Engineer to design, build, and maintain the core platform powering Cube's cloud product, focusing on reliability, scalability, performance, and developer productivity.

You will collaborate with Core and Platform engineers to ensure efficient production operation and a seamless internal experience. This fully remote role is anchored in San Francisco with global reach and open collaboration.

Qualifications

• Strong experience with cloud infrastructure (AWS, GCP, or similar).
• Hands-on experience with Kubernetes, container orchestration, and infrastructure-as-code (Terraform or equivalent).
• Solid understanding of distributed systems, networking, and Linux internals.
• Experience building and operating production systems with high availability and performance requirements.
• Proficiency in at least one programming language used for platform development (Go, Rust, TypeScript, Python, or similar).
• Familiarity with CI/CD systems and release automation.
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.).
• Good communication skills and ability to work effectively in a remote, async environment.
• Background in security best practices for cloud platforms.
• Experience operating data-intensive or analytics-heavy platforms.
• Hands-on use of AI coding tools (Claude Code, Cursor, Copilot, or similar) in your day-to-day engineering workflow.
• Contributions to open-source infrastructure or platform projects.

Responsibilities

• Designing and maintaining cloud-native infrastructure for a globally distributed analytics platform.
• Building internal platform tooling to improve developer velocity, observability, and deployment safety.
• Scaling multi-tenant systems that serve large volumes of analytical queries with strict latency requirements.
• Improving reliability, fault tolerance, and disaster recovery for Cube cloud platform.
• Operating Kubernetes-based environments and evolving our deployment and release pipelines.
• Implementing monitoring, alerting, and incident response practices for a high-availability system.

Skills

Cloud infrastructure

Kubernetes

Distributed systems

Networking

Linux internals

High availability

CI/CD

Observability tools

AI coding tools

Open-source contributions

Tools

AWS

GCP

Terraform

Prometheus

Grafana

OpenTelemetry

GitHub Actions

Job description

At Cube, we're redefining how organizations deliver, consume, and automate data and analytics across teams, tools, and AI agents. Our mission is to enable Agentic Analytics, where AI agents work alongside humans on a shared semantic foundation

If you're fascinated by building core data and AI infrastructure, the kind that powers analytics at the world's most advanced technology companies , but want the agility and ownership of a startup, Cube is where you'll thrive.

With 19,000+ GitHub stars and 13,000+ community members, Cube is trusted by 400+ companies, including Maersk, Kimberly-Clark, Freshworks, Patagonia, Webflow, Brex, Deel, Tubi, Walmart, and Drata. Our platform empowers AI agents with a universal semantic foundation, enabling autonomous analytics at scale while maintaining consistency, security, and performance across BI tools, spreadsheets, and embedded applications.

As a Platform Engineer at Cube, you will be responsible for designing, building, and maintaining the core platform that powers Cube cloud product and supports Cube Core at scale. Your primary focus will be reliability, scalability, performance, and developer productivity across our infrastructure and internal platforms.

You will work closely with Core and Platform engineers to ensure Cube runs efficiently in production environments and provides a seamless experience for our internal teams.

What you will do:

• Designing and maintaining cloud-native infrastructure for a globally distributed analytics platform.
  
• Building internal platform tooling to improve developer velocity, observability, and deployment safety.
  
• Scaling multi-tenant systems that serve large volumes of analytical queries with strict latency requirements.
  
• Improving reliability, fault tolerance, and disaster recovery for Cube cloud platform.
  
• Operating Kubernetes-based environments and evolving our deployment and release pipelines.
  
• Implementing monitoring, alerting, and incident response practices for a high-availability system.
  

Who you are:

• Strong experience with cloud infrastructure (AWS, GCP, or similar).
  
• Hands-on experience with Kubernetes, container orchestration, and infrastructure-as-code (Terraform or equivalent).
  
• Solid understanding of distributed systems, networking, and Linux internals.
  
• Experience building and operating production systems with high availability and performance requirements.
  
• Proficiency in at least one programming language used for platform development (Go, Rust, TypeScript, Python, or similar).
• Familiarity with CI/CD systems and release automation.
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.).
• Good communication skills and ability to work effectively in a remote, async environment.
  
• Background in security best practices for cloud platforms.
  
• Experience operating data-intensive or analytics-heavy platforms.
  
• Hands-on use of AI coding tools (Claude Code, Cursor, Copilot, or similar) in your day-to-day engineering workflow.
  
• Contributions to open-source infrastructure or platform projects.
  

We're a fully remote company based in San Francisco. You can work from anywhere and join our highly collaborative team.