• As a motivated consultant/developer, you help our clients achieve their IT project goals • You consistently onboard yourself into new, complex infrastructures and software projects and independently and responsibly implement new features • Building, operating and extending (cloud) infrastructures are part of your day-to-day responsibilities, just like developing new features • Through knowledge sharing you continuously improve and make both the team and yourself more valuable

• Own our cloud infrastructure across AWS and third-party hosting and compute providers; ensure it is reliable, scalable, and cost-efficient • Own and operate bare-metal compute clusters: node provisioning, configuration management, networking, secure access, and ongoing reliability • Build and maintain configuration management using Ansible (or similar), ensuring reproducible and scalable server provisioning • Set up and maintain Slurm for job scheduling across CPU and GPU node pools; ensure researchers can submit, monitor, and manage jobs without DevOps involvement • Design and manage cluster networking: management and storage networks, inter-node communication, DNS, and secure perimeter access, including bastion/jump host setup • Deep hands-on experience managing Linux-based infrastructure, including networking, firewalls, VPNs, and performance tuning in distributed environments • Own disaster recovery and business continuity: define RTO/RPO targets, maintain runbooks, and run regular tests • Manage and optimize infrastructure spend through capacity planning, right-sizing, and intelligent use of reserved and spot capacity • Manage Kubernetes clusters, networking, and workload scheduling across cloud and on-premise environments • Enable infrastructure-as-code practices in Terraform; drive consistency, modularity, and auditability across the codebase • Evolve our observability platform: improve coverage, reduce alert noise, and ensure engineering teams have the visibility they need to detect and resolve issues quickly • Own security posture across the platform: IAM policies, secrets management, network segmentation, vulnerability management, and SOC 2 compliance • Lead incident management: on-call processes, escalation policies, runbooks, and blameless post-mortems • Drive CI/CD improvements and developer workflow initiatives that meaningfully increase engineering throughput • Evolve internal tooling and CLI infrastructure that engineering teams depend on daily.

• Lead the integration and deployment of global DevOps solutions across private and multi-cloud environments • Design, maintain, and optimize CI/CD pipelines using GitLab CI • Manage Kubernetes-based platforms, ensuring scalability, reliability, and performance • Implement Infrastructure as Code (IaC) using Terraform and Ansible to automate deployments • Build and maintain observability stacks (Prometheus, Grafana, ELK/Loki, OpenTelemetry) • Troubleshoot and resolve issues across application, infrastructure, and network layers • Collaborate with cross-functional and international teams to ensure smooth operations • Drive GitOps automation with ArgoCD / Flux and promote best practices across teams • Enforce security, compliance, and access controls (Vault, RBAC, network policies) • Support hybrid and API-driven infrastructure across multiple cloud environments

• Design, build, and maintain Azure infrastructure using Terraform across dev, staging, and production environments • Own and improve Azure DevOps CI/CD pipelines (YAML), including artefact management, approvals, and automated deployments • Implement and maintain secure Azure networking (VNets, subnets, Private Endpoints, Private DNS, NSGs) to ensure private access to critical services • Configure and enforce security best practices across the platform (RBAC, Managed Identities, Service Principals, Key Vault, secrets handling) • Ensure reliable hosting and operations for platform components (App Service, Functions, Storage, Azure SQL, ACR) • Monitor platform health and performance; troubleshoot incidents using Azure monitoring, logs, and diagnostics • Support the AI processing infrastructure needs, including enabling secure and scalable execution for workflows and batch/experimental pipelines (and optionally Azure ML / Azure OpenAI)