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Open nowPosted 9 days ago

DevSecOps Engineer

MyCareersFuture94,028 open roles

Pay
SGD 7,000 – SGD 9,800 a month
Where
Central, Singapore
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Your applicationOpen nowDevSecOps EngineerMyCareersFuture · Central, Singapore

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  2. 3.3%3 days
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  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 9 days ago

The posting

Company Overview

Vinova is an award-winning development company specializing in mobile, web, and enterprise applications. Since 2010, we serve global clients across IoT, blockchain, fintech, and ecommerce, delivering quality, flexible, and fast solutions through passionate collaboration.

Job Summary

You will lead the management and scaling of AWS cloud environments and production-grade Kubernetes on AWS EKS, ensuring secure, reliable, and compliant infrastructure operations aligned with stringent regulatory requirements.

Responsibilities

  • Manage and scale AWS cloud environments, taking full ownership of Kubernetes cluster architecture, workload deployment, security, upgrades, autoscaling, resilience, observability, and incident troubleshooting on AWS EKS
  • Provision, configure, and administer AWS services including RDS PostgreSQL, OpenSearch, Bedrock AI services, and ELB to support application needs
  • Design, operate, and troubleshoot secure AWS network architectures in regulated, multi-account environments, applying network segmentation, least-privilege principles, and connectivity solutions such as VPN and Direct Connect
  • Establish and maintain service-level indicators and objectives, dashboards, alerts, logs, metrics, and distributed traces for infrastructure, Kubernetes, applications, and AI workloads
  • Lead incident response, root-cause analysis, corrective actions, capacity planning, backup and restore testing, and disaster-recovery exercises to meet recovery objectives
  • Use Terraform to provision and manage repeatable AWS and Kubernetes environments as Infrastructure as Code
  • Administer and optimize GitLab CI/CD pipelines with automated testing, security scans (SAST, DAST), policy enforcement, approval controls, rollback mechanisms, and auditable release records
  • Embed security controls throughout the platform lifecycle, including threat modeling, secure architecture reviews, vulnerability and patch management, penetration testing, remediation tracking, audit evidence, and technical risk assessments
  • Collaborate with cybersecurity, governance, product, and project teams to translate government security requirements and enterprise standards into automated, testable controls
  • Implement least-privilege IAM, workload identity, privileged-access controls, secrets and certificate management, container image signing and scanning, software bills of materials, dependency governance, and policy enforcement across infrastructure and deployment pipelines
  • Protect sensitive configurations and credentials while maintaining traceability of changes and releases
  • Collaborate with external vendors to map current architecture, reverse-engineer undocumented configurations, and transition infrastructure operations fully in-house

Required competencies and certifications

  • Hands-on experience in DevOps, DevSecOps, Cloud Engineering, or similar roles with 2 to 5+ years of relevant production experience
  • Proficiency with Kubernetes and Terraform in production environments
  • Strong expertise in AWS infrastructure, including AWS EKS and Kubernetes networking
  • Deep knowledge of complex AWS networking in multi-account and regulated environments
  • Experience building and maintaining CI/CD pipelines
  • Proven ability to define service-level objectives, build monitoring and alerting systems, respond to production incidents, conduct root-cause analysis, manage capacity, and design/test backup, restore, and disaster-recovery plans
  • Experience delivering or operating systems under Singapore Government Commercial Cloud and IM8 requirements or similarly stringent regulatory frameworks

Preferred competencies and qualifications

  • Significant hands-on experience deploying and operating agentic AI workloads
  • Familiarity with production AI and machine-learning workloads
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