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 both internal teams and customers.

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.