Cloud Engineer – Confidential AI Workloads

About the role

We are looking for a Cloud Engineer to join our client’s Enterprise AI Foundation and enable secure, production‑ready AI workloads on Azure. Working remotely with occasional trips to the Netherlands, you will translate high‑level architecture into operational cloud environments that protect confidential data at every layer.

Key responsibilities

• Implement workloads within a Confidential Landing Zone under senior guidance.
• Execute end‑to‑end workload onboarding, including CMDB registration, budget validation and production go‑live.
• Design and implement solution architecture covering data access, network topology and AKS configuration, including confidential GPU nodes.
• Perform and document security and compliance activities such as threat modelling, CSF control validation and risk assessments.
• Coordinate vulnerability remediation and penetration testing prior to production.
• Build infrastructure as code using Terraform and automate deployments with Helm and CI/CD pipelines.
• Configure and operate observability tooling (Prometheus, Loki, Grafana).
• Maintain operational readiness, business continuity and disaster recovery plans.
• Collaborate with CCoE Security and supporting architects on architecture changes.

Required profile

• Minimum 4 years of experience working in Azure environments.
• Experience with Cloud Landing Zones (CAF / Enterprise Scale).
• Proven ability to work in a governed enterprise environment with a focus on quality and reliability.

Required skills

• Azure cloud platform.
• Terraform and Infrastructure as Code.
• Azure Kubernetes Service (AKS) and Kubernetes.
• Confidential GPU nodes for AI processing.
• Networking concepts: VNet, subnets, private endpoints, DNS.
• Helm, CI/CD pipelines.
• Observability tools: Prometheus, Loki, Grafana.
• Security and compliance processes: threat modelling, risk assessments, CSF control validation.