Cloud DevOps Engineer

• 5+ years operating cloud-based production systems

• Strong Kubernetes orchestration experience

• Hands-on Terraform and Infrastructure as Code expertise

• CI/CD pipeline experience (GitLab)

• AWS or GCP experience

• Scripting and automation (Python, YAML, JSON, Bash)

• Experience with observability tools

• Strong Linux knowledge

• Experience with AIOps platforms or ML-assisted monitoring

• AI-assisted DevOps or Cloud Operations exposure

• IAM or regulated environment experience

• ITIL or COBIT familiarity

• Experience in globally distributed teams

• Bachelor's degree in Computer Science, Engineering, or equivalent experience

Location: Amersfoort CDI, Netherlands

Thales delivers global, high-availability cloud-based Identity and Access Management (IAM) services for high-profile customers, operating under the highest security and compliance standards.
To support continued customer growth and increasing platform complexity, Thales is seeking a Senior Cloud DevOps Engineer to join the Cloud Operations organization. This role is responsible for the reliability, scalability, automation, and continuous improvement of IAM cloud infrastructure and platforms across AWS and GCP, with a strong focus on automation, observability, and AI-assisted operations (AIOps).

Cloud Operations & Reliability Engineering

• Operate and support production-grade, highly available IAM cloud services

• Ensure availability, performance, resilience, and security of platforms

• Participate in L2/L3 incident response, root-cause analysis, and post-incident reviews

• Take part in a 24/7 follow-the-sun on-call rotation

• Drive continuous improvements to operational stability and service quality

• Design, implement, and maintain Infrastructure as Code (IaC) using Terraform

• Build and maintain CI/CD pipelines (GitLab)

• Deploy and manage Kubernetes-based platforms (EKS, GKE, OpenShift)

• Automate provisioning, deployment, validation, and rollback processes

• Review DevOps code to ensure quality, security, and consistency

• Implement monitoring, logging, and alerting using Datadog

• Leverage AIOps capabilities for anomaly detection and alert correlation

• Support faster root-cause identification during incidents

• Contribute to predictive analytics such as capacity forecasting and failure prevention

• Use AI-powered copilots for troubleshooting and diagnostics

• Generate and improve operational documentation and runbooks using AI

• Develop automated remediation and self-healing workflows

• Integrate AI-assisted insights into operational workflows

• Support cloud databases: PostgreSQL, MySQL, MSSQL, MongoDB, Elastic

• Contribute to upgrades, backups, HA/DR, and monitoring

• Assist with data migrations where required

• Ensure database security and performance

• Produce design documents, runbooks, and operational procedures

• Collaborate with Automation Architects, SREs, and R&D teams

• Improve scalability, reliability, security, and cost efficiency

• Follow ITIL-aligned operational processes

• Operate in regulated and security-sensitive environments

• Cloud: AWS, GCP

• Platforms: Kubernetes, Helm, OpenShift

• IaC & Automation: Terraform, Ansible

• CI/CD: GitLab

• Observability: Datadog

• Collaboration: Jira, Confluence, Slack, Office 365

• AI Tooling: AIOps platforms, internal AI copilots

• Ownership and accountability

• Clear communication

• Calm under pressure

• Continuous improvement mindset

• Comfortable working across time zones