DevSecOps Engineer

CAPGEMINI SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Capgemini Singapore Pte. Ltd. seeks an experienced DevSecOps Engineer to own the security, reliability, scalability, and compliance of its cloud and Kubernetes environments, deployment pipelines, and AI workload infrastructure.

You will be the primary technical owner of our AWS and Kubernetes platform, bridging software development, AI engineering, cybersecurity, governance, and production operations. Responsibilities include end-to-end ownership of AWS/Kubernetes, network security design, IaC

Qualifications

• Hands-on security-focused DevSecOps mindset for cloud/infrastructure
• Experience bridging software development, security, and operations
• Strong understanding of CI/CD practices and automation tools

Responsibilities

• Own cloud infrastructure and Kubernetes platform architecture and reliability
• Manage AWS services, network security, and regulated multi-account environments
• Implement IaC (Terraform) and automate CI/CD pipelines with GitLab
• Embed security controls, vulnerability management, and threat modelling across the stack
• Collaborate with AI engineering, governance and production operations teams

Skills

DevSecOps

Cloud Engineering

CI/CD

Tools

Terraform

Kubernetes

Job description

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.

About the Role

We are looking for an experienced DevSecOps Engineer to own the security, reliability, scalability, and compliance of our cloud and Kubernetes environments, deployment pipelines, and AI workload infrastructure. In this role, you will be the primary technical owner of our AWS and Kubernetes platform, bridging software development, AI engineering, cybersecurity, governance, and production operations. You will establish secure engineering guardrails, automate repeatable controls, and build resilient platform capabilities that enable teams to deploy and operate Generative AI workloads safely at scale.

Responsibilities

• Cloud Infrastructure & Kubernetes Ownership: Manage and scale our AWS cloud environments and take end-to-end ownership of production-grade Kubernetes on AWS EKS, including cluster architecture, workload deployment, security, upgrades, autoscaling, resilience, observability, and incident troubleshooting.
• AWS Ecosystem Administration: Provision, configure, and manage essential AWS services supporting our applications. This includes managed relational databases (RDS PostgreSQL), search/analytics (OpenSearch), AI services (Bedrock), and networking/load balancing (ELB).
• Network Architecture, Security & Connectivity: Design, operate, and troubleshoot secure AWS network architectures for regulated, multi-account environments. This includes VPC and subnet design, CIDR planning, Transit Gateway routing and route-table segmentation, centralized ingress and egress, AWS Network Firewall and WAF, security groups and network ACLs, private connectivity through VPC endpoints or AWS PrivateLink, DNS resolution, load balancing, and connectivity to shared services or on-premises networks through VPN or Direct Connect. Apply network segmentation and least-privilege principles across production, non-production, management, and shared-service environments.
• Production Reliability, Observability & Resilience: Establish service-level indicators and objectives, dashboards, alerts, logs, metrics, and distributed traces across 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 agreed recovery objectives.
• Infrastructure as Code, CI/CD & Automation: Use Terraform as the primary Infrastructure as Code tool to provision and manage repeatable AWS and Kubernetes environments. Administer and optimise GitLab CI/CD pipelines with automated testing, SAST, DAST, dependency and container scanning, policy checks, approval controls, immutable artefacts, environment promotion, rollback mechanisms, and auditable release records.
• Compliance, Security Engineering & Vulnerability Management: Embed security controls throughout the platform lifecycle, including threat modelling, secure architecture reviews, vulnerability and patch management, penetration testing, hardening, remediation tracking, audit evidence, and technical risk assessments. Work with cybersecurity, governance, product, and project stakeholders to translate government security requirements and enterprise standards into automated, testable controls.
• Identity, Secrets & Software Supply Chain Security: 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 configuration and credentials, and maintain traceability of changes and releases.
• Vendor Transition: Work closely alongside existing external vendors to map the current architecture, reverse-engineer undocumented configurations, and safely transition infrastructure operations fully in-house.

Requirements

Experience: Typically 2 to 5+ years of hands-on experience in DevOps, DevSecOps, Cloud Engineering, or a similar role. We welcome candidates with fewer years of experience who can demonstrate strong practical capability, sound engineering fundamentals, and ownership of production systems. Hands-on production experience with Kubernetes and Terraform is mandatory; depth of capability and evidence of impact will be valued over years of service. Cloud & Kubernetes: Strong proficiency i