Software Engineer, Cloud Platform

The Role

Join Cloud Platform Engineering to own the Kubernetes fleet that runs our production AI workloads. You’ll turn manual cluster operations into reliable, repeatable systems-from bringing new cloud providers online to rolling out configuration and upgrades safely across the entire fleet.

This is a hands-on software engineering role with ownership from design through production. You’ll build APIs, controllers, and automation that make infrastructure easier to operate, reduce configuration drift, and bring GPU capacity online seamlessly to power the AI inference business growth.

Example Initiatives

• Unify Kubernetes platform configuration under GitOps, replacing duplicated cluster manifests with shared configuration and explicit provider overrides.
• Automate cluster onboarding and provisioning with reusable infrastructure templates, readiness checks, and recoverable workflows.
• Build controllers and rollout mechanisms for fleet upgrades and workload-aware maintenance.

Responsibilities

• Design, build, and operate services, APIs, and Kubernetes controllers that automate cluster lifecycle management.
• Develop reusable Terraform modules and GitOps configuration that work across cloud and GPU infrastructure providers.
• Make infrastructure changes safe through validation, staged rollouts, clear ownership boundaries, and tested recovery paths.
• Build observability into automation so engineers can understand progress, diagnose failures, and retry operations safely.
• Partner with infrastructure and workload teams to define platform interfaces, resolve operational pain points, and take projects from design through adoption.

Requirements

• Experience building and owning production infrastructure software or distributed systems.
• Strong programming skills in Go or another systems or backend language, with the ability to contribute to a Go codebase.
• Deep experience with Kubernetes infrastructure, including developing controllers or operators and understanding reconciliation, custom resources, and failure handling.
• Practical experience with infrastructure as code and GitOps tools such as Terraform and Flux or Argo CD.
• Strong Linux, networking, and debugging fundamentals, with sound judgment about reliability and the impact of production changes.
• Ability to turn ambiguous operational problems into maintainable software and communicate design tradeoffs clearly.

Nice to Have

• Experience managing Kubernetes fleets across multiple clouds or GPU infrastructure providers.
• Contributions to Kubernetes or infrastructure open source projects, or experience with workflow orchestration and progressive delivery.

Benefits

• Competitive compensation, including meaningful equity
• (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
• Paid parental leave
• Fertility and family-building stipend through Carrot
• (U.S. only) Company-facilitated 401(k)
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.