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evolution recruitment solutions pte. ltd.

DevOps/DevSecOps Engineer

4-6 Years
SGD 7,500 - 10,000 per month
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  • Posted 5 days ago
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Job Description

Key Responsibilities

Cloud Infrastructure & Automation

  • Design, deploy, and maintain cloud environments on AWS or GCP.
  • Develop and manage infrastructure using Infrastructure-as-Code tools such as Terraform or similar technologies.
  • Implement secure networking architectures, including VPCs, private connectivity, VPNs, peering, and network segmentation.
  • Establish scalable multi-environment and multi-account cloud strategies.

Container Platform & Kubernetes

  • Build and manage Kubernetes environments for production workloads.
  • Configure cluster security, RBAC, autoscaling, workload isolation, and governance controls.
  • Create standardized deployment frameworks for microservices, backend services, and AI-related workloads.
  • Support both real-time and batch processing environments.

CI/CD & Release Automation

  • Design and optimize CI/CD pipelines to streamline software delivery.
  • Implement automated testing, deployment validation, and release management processes.
  • Support deployment strategies such as blue-green, canary, and phased rollouts.
  • Improve developer productivity through automation and deployment standardization.

Observability & Site Reliability

  • Implement monitoring, logging, tracing, and alerting solutions.
  • Define service reliability metrics, performance objectives, and operational standards.
  • Support incident response processes, root-cause analysis, and continuous service improvement.
  • Develop operational runbooks and support on-call readiness.

Security & DevSecOps

  • Strengthen cloud security through identity and access management best practices.
  • Manage secrets, certificates, and sensitive configuration securely.
  • Implement vulnerability scanning, dependency analysis, and container security controls.
  • Enforce security policies through automation and governance frameworks.
  • Support audit readiness and compliance requirements.

AI/ML Platform Support

  • Collaborate with data science and machine learning teams to operationalize AI solutions.
  • Support model deployment, inference services, batch processing, and ML infrastructure.
  • Monitor performance, availability, and resource consumption of AI workloads.
  • Contribute to platform capabilities that improve AI product scalability.

Cost Optimization

  • Monitor cloud spending and resource utilization.
  • Implement tagging, budgeting, and optimization initiatives.
  • Drive efficiency improvements without compromising performance or reliability.

Developer Experience

  • Build self-service infrastructure capabilities and reusable engineering templates.
  • Improve internal tooling and automation workflows.
  • Maintain clear technical documentation and operational guidelines.
  • Help create a smooth developer experience across engineering teams.

Requirements

Essential Skills & Experience

  • Minimum 4 years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or related infrastructure roles.
  • Strong hands-on experience with AWS or Google Cloud Platform.
  • Proven expertise with Infrastructure-as-Code tools, preferably Terraform.
  • Solid Kubernetes administration and containerization experience (Docker, Helm, Kustomize, etc.).
  • Strong knowledge of CI/CD pipelines and modern software delivery practices.
  • Good understanding of Linux systems, networking, and automation scripting using Python and/or Bash.
  • Experience implementing monitoring, logging, and observability solutions.
  • Strong understanding of cloud security principles, IAM, secrets management, and infrastructure hardening.
  • Ability to collaborate effectively with software engineers, product stakeholders, and technical leadership.
  • Strong documentation and communication skills.

Preferred Qualifications

  • Experience with GitOps practices and tools such as ArgoCD or Flux.
  • Exposure to policy-as-code and infrastructure testing frameworks.
  • Familiarity with data engineering or machine learning ecosystems.
  • Experience working with distributed systems, streaming platforms, or large-scale data processing technologies.
  • Knowledge of enterprise compliance, governance, and security review processes.
  • Exposure to reliability engineering practices such as resilience testing or disaster recovery exercises.

More Info

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Job ID: 148707457

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