Scale AI

Senior Infrastructure Software Engineer, Apps Platform

Scale AI
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6 hours ago
London, United KingdomSenior

Responsibilities

  • Expand platform deployment coverage across AWS, Azure, GCP, OCI, other cloud providers, and on-premises environments.
  • Build secure, fast, reproducible deployment pipelines and improve platform observability.
  • Partner with internal teams to understand deployment needs, debug issues, and develop supporting tooling.
  • Respond to production incidents, conduct root cause analysis, and implement preventive fixes.
  • Help maintain the deployment and observability product roadmap.
  • Lead architecture reviews and own projects from design through deployment.

Requirements

  • 7+ years of experience building and deploying enterprise and public sector solutions across major cloud providers and on-premises environments.
  • Deep expertise in infrastructure design, networking, VPNs, load balancers, and firewalls.
  • Deep proficiency with infrastructure-as-code, containerization, orchestration, Kubernetes, Terraform, and Docker.
  • Experience with CI/CD pipelines and software delivery using GitHub Actions or CircleCI.
  • Experience with GitOps-style deployments and consistent, repeatable releases.
  • Strong production debugging skills and ability to navigate performance and security tradeoffs.
  • Preferred experience includes founding or joining an infrastructure startup early, running secure workloads in multi-tenant or untrusted environments, contributing to systems or developer-tools open source projects, and handling production on-call or incident response.

Categories

Scale AI

About Scale AI

5,001-10,000 employees

Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.

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