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Platform Engineer at Cube Dev

Roles & Responsibilities

  • 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.

Requirements:

  • 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.
  • Operating Kubernetes-based environments and evolving our deployment and release pipelines.

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 companies like SecurityScorecard, Webflow, The Linux Foundation, Cloud Academy, and SamCart.Our platform empowers AI agents with a universal semantic foundation — enabling autonomous analytics at scale while maintaining the same 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.

  • 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, Python, or similar).

  • Good communication skills and ability to work effectively in a remote, async environment.

  • Fluent English.

Bonus points:

  • Experience operating data-intensive or analytics-heavy platforms.

  • Familiarity with CI/CD systems and release automation.

  • Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.).

  • Background in security best practices for cloud platforms.

  • 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.

Cube does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. If you need reasonable accommodations during the interview process, please discuss this with the recruiter and we'll gladly work with you.

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