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Open nowPosted 6 days ago

DevSecOps Engineer (GenAI)

MyCareersFuture94,028 open roles

Pay
SGD 5,500 – SGD 6,500 a month
Where
Central, Singapore
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Your applicationOpen nowDevSecOps Engineer (GenAI)MyCareersFuture · Central, Singapore

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 6 days ago

The posting

We are seeking a DevSecOps Engineer to manage the security, reliability, scalability, and compliance of cloud platforms, Kubernetes environments, CI/CD pipelines, and AI infrastructure. This role will drive secure platform operations, infrastructure automation, and cloud governance while enabling the safe deployment of Generative AI workloads.

Key Responsibilities

Cloud & Kubernetes Platform

  • Manage and scale AWS environments and Kubernetes clusters on Amazon EKS.
  • Own cluster architecture, deployment, security, upgrades, autoscaling, monitoring, and incident resolution.
  • Ensure platform reliability, resilience, and operational readiness.

AWS Infrastructure & Networking

  • Administer AWS services including RDS PostgreSQL, OpenSearch, Bedrock, and ELB.
  • Design and support secure AWS network architectures, covering VPCs, subnets, Transit Gateway, firewalls, WAF, PrivateLink, VPN, Direct Connect, DNS, and load balancing.
  • Apply network segmentation and least-privilege principles.

Reliability, Monitoring & Operations

  • Establish SLI/SLO frameworks, monitoring dashboards, alerting, logging, metrics, and tracing.
  • Lead incident management, root cause analysis, capacity planning, backup validation, and disaster recovery testing.

Infrastructure Automation & CI/CD

  • Build and manage AWS and Kubernetes environments using Terraform.
  • Maintain GitLab CI/CD pipelines with:Automated testingSAST / DASTDependency and container scanningPolicy enforcementRelease approvalsRollback mechanismsAudit-ready deployment records

Security & Compliance

  • Implement security controls throughout the platform lifecycle.
  • Conduct threat modelling, architecture reviews, vulnerability management, patching, hardening, risk assessments, and audit support.
  • Translate regulatory and security requirements into automated platform controls.

Identity & Supply Chain Security

  • Manage IAM, workload identities, privileged access, secrets, certificates, container security, SBOMs, and dependency governance.
  • Ensure secure handling of credentials and platform changes.

Platform Transition & Documentation

  • Review existing platform architecture and operational configurations.
  • Support infrastructure knowledge transfer and operational transition activities.
  • Maintain architecture diagrams, runbooks, procedures, and technical documentation.

Requirements

Experience

  • 2 to 5+ years of experience in DevOps, DevSecOps, Cloud Engineering, or related roles.
  • Strong hands-on experience with Kubernetes and Terraform in production environments.

Technical Skills

  • Strong AWS infrastructure and Amazon EKS expertise.
  • Experience with Kubernetes networking, ingress controllers, load balancers, service discovery, network policies, and connectivity troubleshooting.
  • Strong knowledge of AWS networking, including VPCs, Transit Gateway, PrivateLink, Route 53, VPN, Direct Connect, Security Groups, and Network ACLs.
  • Experience designing and maintaining GitLab CI/CD pipelines.

Operational Excellence

  • Experience with monitoring, alerting, incident response, root cause analysis, capacity management, backup and recovery, and disaster recovery planning.

Regulated Environments

  • Experience supporting platforms within highly regulated environments.
  • Understanding of governance, audit requirements, change management, risk management, segregation of duties, and secure data handling.

Communication

  • Ability to communicate technical concepts to both technical and business stakeholders.
  • Strong documentation skills, including architecture diagrams, operational procedures, runbooks, and risk assessments.

Preferred Skills

  • Experience operating AI or agentic AI platforms.
  • Familiarity with agent observability, distributed tracing, prompt management, evaluation pipelines, and secure model integrations.
  • Experience supporting production AI/ML workloads, including monitoring latency, usage, cost, and responsible AI controls.
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