DevOps Engineer – AI Inference

Gcore

DevOps Engineer for Gcore designing and maintaining infrastructure for AI inference workloads. Collaborating with ML engineers and platform teams on scalable AI solutions.

Posted 7/1/2026full-timeRemote • 🇵🇱 PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining infrastructure for AI inference workloads, with strong capabilities in Kubernetes management, automation tooling, and CI/CD pipeline implementation. Proficient in monitoring and observability for AI platforms, ensuring optimal system performance and model health.

Highest-signal resume keywords

Kubernetes Cluster ManagementCI/CD Pipeline ImplementationInfrastructure Provisioning with TerraformAutomation Development using PythonMonitoring Tools for AI Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

KubernetesPythonGoBashTerraformAnsibleGitLab CIGitHub ActionsLinux SystemsNetworking Concepts

Tools & Technologies

HelmDockerPrometheusSlurmArgo CDHelmfileCluster API

Industry Keywords

AI Inference WorkloadsModel Deployment PipelinesMonitoring and ObservabilityData Access PatternsSystem Architecture

Tech Stack

Tools & technologies

AnsibleCloudDockerGoKubernetesLinuxPrometheusPythonTerraform

About the role

Key responsibilities & impact

Design, develop, and maintain infrastructure for AI inference workloads, including GPU scheduling, model deployment pipelines, and data access patterns in on-prem environments
Build and manage monitoring and observability tools for AI inference platforms, including dashboards, alerts, and runbooks for model health and system performance
Collaborate with ML engineers and platform teams to design system architecture for AI workloads, integrate inference runtimes, and test performance at scale

Requirements

What you’ll need

Hands-on experience deploying, operating, and troubleshooting Kubernetes clusters, including Helm, Docker, or CRI-O.
Strong understanding of Linux systems and networking concepts, including troubleshooting connectivity and performance issues.
Ability to develop automation and operational tooling using Python, Go, or Bash.
Experience provisioning and managing infrastructure with tools such as Terraform and Ansible.
Experience designing, implementing, and maintaining CI/CD pipelines using GitLab CI or GitHub Actions.
Preferred Qualifications
Experience operating or administering Slurm clusters.
Experience with Cluster API (CAPI) or other Kubernetes cluster lifecycle management ("Kubeception") technologies.
Deep understanding of Kubernetes internals, including CNI, CSI, Operators, and cluster architecture.
Nice to Have
Experience with Kubernetes ecosystem tools such as Argo CD and Helmfile.
Experience with Prometheus.
Familiarity with other Cloud Native technologies

Benefits

Comp & perks

Competitive compensation
Flexible working hours and hybrid or remote options, depending on your role
Work from anywhere in the world for up to 45 days per year
Private medical insurance for you and your family*
Extra paid vacation and sick leave days*
Support for life’s important moments and celebrations
Language courses to help you connect and grow
Modern, welcoming offices with snacks, drinks, and entertainment*
Team sports and social activities*