Platform / DevOps Engineer

Selby Jennings; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Selby Jennings is seeking a highly hands-on DevOps / Platform Engineer to design, build, and manage the organisation's container and cloud platform, with a focus on production-grade Kubernetes.

The role covers cluster lifecycle, networking, security, observability, and automation, plus GitOps and CI/CD pipelines, enabling scalable AI workloads and reliable operations across environments.

Qualifications

• Hands-on DevOps/platform engineering with cloud infra experience.
• Experience owning Kubernetes clusters through full lifecycle.
• Familiarity with IaC tools like Terraform, Pulumi, or CloudFormation.
• Automation and configuration management with Ansible.
• Knowledge of CI/CD, GitOps, and security baselines.

Responsibilities

• Design and build Kubernetes clusters across dev, test, staging, and prod.
• Provision and configure clusters using managed or self-managed distributions.
• Own installation, scaling, upgrades, backup, and decommissioning.
• Manage cluster networking, ingress, DNS, storage, and PVs.
• Implement RBAC, secrets, network policies, and image security.
• Build reusable platform services and automation via IaC.
• Define governance standards and production-readiness requirements.
• Develop CI/CD and GitOps pipelines with GitHub Actions, Argo CD, etc.
• Support AI workloads and GPU-based clusters where applicable.

Skills

DevOps

Platform engineering

Kubernetes

IaC

Ansible

GitOps

Linux

Networking

Security

Observability

Tools

Terraform

Pulumi

CloudFormation

Ansible

Helm

GitHub Actions

GitLab CI

Jenkins

Argo CD

Flux

Prometheus

Grafana

OpenSearch

Datadog

Splunk

Job description

We are looking for a highly hands-on DevOps / Platform Engineer to design, build, and manage the organisation's container and cloud platform.

The successful candidate will have direct experience building, provisioning, configuring, upgrading, securing, and operating Kubernetes clusters in production environments.

You will be responsible for the underlying platform, including cluster architecture, networking, storage, security, governance, observability, automation, and reliability. Exposure to AI infrastructure, MLOps, GPU-enabled environments, or the deployment of AI workloads would be advantageous.

Key Responsibilities

• Design and build Kubernetes clusters across development, testing, staging, and production environments.
• Provision and configure Kubernetes clusters using managed services or self-managed distributions.
• Own the full Kubernetes cluster lifecycle, including installation, configuration, scaling, patching, version upgrades, backup, recovery, and decommissioning.
• Manage Kubernetes control-plane and worker-node architecture, cluster capacity, availability, and performance.
• Configure and maintain cluster networking, ingress controllers, DNS, load balancing, service discovery, storage classes, and persistent volumes.
• Implement Kubernetes security controls, including RBAC, secrets management, network policies, pod security standards, image security, and admission controls.
• Build and maintain reusable container platform services for engineering and application teams.
• Develop automated cluster-provisioning and configuration-management processes using Infrastructure as Code.
• Establish platform governance standards, security baselines, naming conventions, deployment policies, and production-readiness requirements.
• Define and maintain reusable templates, Helm charts, platform blueprints, and golden paths.
• Build and manage CI/CD and GitOps capabilities using tools such as GitHub Actions, GitLab CI, Jenkins, Argo CD, or Flux.
• Manage container registries, image lifecycle processes, vulnerability scanning, and software-supply-chain controls.
• Partner with security, infrastructure, architecture, and engineering teams to ensure the platform meets governance and compliance requirements.
• Support production incidents and drive root-cause analysis and long-term remediation.
• Evaluate and introduce new platform technologies that improve scalability, security, reliability, and developer productivity.
• Support AI and machine-learning workloads, including GPU-based clusters, containerised model deployment, model-serving platforms, and MLOps pipelines where applicable.

Requirements

• Strong hands-on experience in DevOps, platform engineering, cloud infrastructure, or site reliability engineering.
• Proven experience building and managing Kubernetes clusters, rather than only deploying applications onto existing clusters.
• Experience owning Kubernetes clusters through their full operational lifecycle.
• Experience with Infrastructure as Code tools such as Terraform, Pulumi, CloudFormation, or similar technologies.
• Experience with configuration-management and automation tools such as Ansible.
• Experience with Helm, Kubernetes Operators, GitOps, and automated cluster deployment.
• Strong knowledge of Linux administration, networking, infrastructure security, identity and access management, and production operations.
• Experience defining governance controls, platform standards, security baselines, and operational policies.
• Familiarity with observability tools such as Prometheus, Grafana, ELK, OpenSearch, Datadog, or Splunk.