Engineering Manager, Infrastructure

Scale AI
London
Workplace: OnsiteFull timeFunction: DevOps, Cloud & InfrastructureExperience: 5+ yearsSkills: ["Leadership","Mentoring","Technical delivery","Collaboration","Communication"]

Lead infrastructure engineering for the Enterprise team, owning the deployment lifecycle from rollout through long-term operational health. Define and execute infrastructure roadmaps, design secure and reliable systems, and manage engineering delivery. Set SLAs/SLOs for uptime and performance, and build backend services supporting AI agents, evaluation tooling, and automation. Partner with product and security leaders to translate deployment challenges into scalable improvements, playbooks, and developer experience.

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FursaFursa
Scale AI
Scale AI
1 month ago

Engineering Manager, Infrastructure

✓ Verified Job

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Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Lead infrastructure engineering for the Enterprise team, owning the deployment lifecycle from rollout through long-term operational health. Define and execute infrastructure roadmaps, design secure and reliable systems, and manage engineering delivery. Set SLAs/SLOs for uptime and performance, and build backend services supporting AI agents, evaluation tooling, and automation. Partner with product and security leaders to translate deployment challenges into scalable improvements, playbooks, and developer experience.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Manager level

Key Responsibilities

  • •Define and execute the infrastructure roadmap aligned with business and engineering priorities.
  • •Lead design and implementation of scalable, secure, and reliable infrastructure systems.
  • •Set and maintain SLAs/SLOs for platform uptime, performance, and developer experience.
  • •Manage the engineering team and drive technical delivery.
  • •Design, build, and optimize backend services for AI-driven applications, including AI agents, evaluation tooling, and automation.

Key Requirements

  • •At least 5 years of relevant experience, including 2+ years managing infrastructure or platform teams.
  • •Proven cloud experience with AWS, GCP, Azure, or OCI.
  • •Experience with Kubernetes deployments on on-prem infrastructure.
  • •Deep understanding of CI/CD pipelines (CircleCI, GitHub Actions), infrastructure-as-code (Terraform), and container orchestration (Kubernetes).
  • •Experience managing production environments with high availability, reliability, and scalability, plus monitoring/alerting and incident response basics.
Experience:5+ yearsEnterprise SaaSOn-premPlatform engineering
Skills:LeadershipMentoringTechnical deliveryCollaborationCommunication
Languages:English
Tech Stack:AWSGCPAzureOCIKubernetesCircle CIGitHub ActionsTerraformCI/CDInfrastructure-as-codeOn-prem infrastructure

Company Brief

Scale AI
Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2016
WebsiteLinkedIn