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Encord

AI-native data infrastructure for Physical AI

DevOps Engineer

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • At least 4 years of hands-on DevOps, platform engineering, or site reliability engineering experience in a production environment.
  • Strong experience building and maintaining continuous integration and continuous delivery pipelines and deployment automation at scale.
  • Proven experience with infrastructure-as-code tools such as Terraform or Pulumi, and configuration management.
  • Strong fundamentals in designing, building, and maintaining resilient distributed or high-performance systems.
  • Hands-on experience with Kubernetes and containerized workloads in cloud environments using Google Cloud Platform and/or Amazon Web Services.
  • Solid understanding of networking, operating systems, and database technologies.
  • Experience with observability fundamentals, including metrics, logs, traces, and alerting.

Responsibilities

  • Own and continuously improve deployment pipelines; partner with developers to review infrastructure changes, streamline release processes, and champion DevOps best practices across the engineering group.
  • Design, deploy, and maintain cloud infrastructure on Google Cloud Platform and Amazon Web Services; manage Kubernetes clusters, networking, and storage at petabyte scale, using infrastructure as code by default.
  • Build, guide, and review automation and internal tooling efforts across the engineering group to improve developer productivity and eliminate manual toil.
  • Profile and optimize services handling large-scale data pipelines; perform capacity planning for storage- and compute-intensive workloads; work with squads to establish performance benchmarks and expectations.
  • Define and own service-level indicators, service-level objectives, and service-level agreements for critical services; build alerting, runbooks, and incident response processes; lead blameless postmortems.
  • Instrument services with distributed tracing, logging, and metrics using tools such as Prometheus, Grafana, OpenTelemetry, and Google Cloud dashboards; build infrastructure, define best practices, and work with each squad to ensure services are observable before production.

About the Company

Encord

AI-native data infrastructure for Physical AI

Encord provides an AI-native data infrastructure platform for Physical AI, helping enterprises manage multimodal data for robotics, autonomous systems, and related applications. It offers Encord Annotate for collaborative multimodal annotation, Encord Active for data curation and quality evaluation, and Encord Index for petabyte-scale dataset search and management, covering the full data lifecycle from collection to deployment. The platform acts as a universal data layer for production-grade Physical AI, addressing the infrastructure gap left by cloud-era tools focused on text and tabular data and emphasizing multimodal data and embodied AI. Its goal is to enable teams to build, evaluate, and deploy real-world AI systems more efficiently with scalable, reliable data tooling.

Company size
201-500
Company stage
Series C
Total funding
$107.1M
Headquarters
London, United Kingdom
Founded
2020

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