Sovereign Engineering Platform SRE (m/f/d)

Job Description

Key responsibilities

Build and operate Kubernetes environments that host AI engineering tools, internal model gateways, retrieval components, workflow services, CI/CD runners, and documentation services. Implement GitOps and Infrastructure as Code patterns for reproducible provisioning, configuration, policy enforcement, platform upgrades, and disaster recovery readiness. Manage private registries, package mirrors, secrets, identity integration, network segmentation, storage classes, backup routines, and controlled connectivity models. Provide observability for engineering workloads, including metrics, logs, traces, GPU and CPU utilization, service health, cost signals, and operational runbooks. Work with software, security, and architecture teams to ensure the platform supports AI-assisted SDLC workflows without creating uncontrolled data exposure or audit gaps.

Examples of market tools, models, and platform components expected

• Platform tooling such as Kubernetes, Helm, Terraform, Ansible, ArgoCD, Crossplane, GitLab runners, Jenkins agents, private registries, and internal package mirrors.

• AI platform components such as vLLM, Ollama, OpenAI-compatible gateways, Qdrant or similar vector stores, OpenWebUI, Continue-compatible endpoints, and workflow services.

• Observability and operations stacks such as Prometheus, Grafana, Loki, OpenTelemetry, ELK/OpenSearch, Alertmanager, SRE runbooks, and incident management tooling.

• Security and governance components such as Vault, Keycloak, network policies, RBAC, admission controls, image scanning, SBOM tooling, and audit logging.

• Infrastructure awareness covering GPU-backed nodes, CPU-only fallback, storage performance, network isolation, proxy patterns, on-premise environments, and dedicated landing zones.

Qualifications

• 5+ years in SRE, platform engineering, DevOps, cloud infrastructure, or operations roles with strong Kubernetes and Linux expertise.

• Proven experience building and operating production-grade engineering platforms with GitOps, Infrastructure as Code, observability, and operational runbooks.

• Hands-on skills in Terraform, Ansible, Helm, Python or shell scripting, CI/CD runners, private registries, and secure configuration management.

• Good understanding of networking, storage, secrets, access control, monitoring, backup, disaster recovery, and operational hardening in high-security environments.

• Comfortable supporting AI-enabled engineering workloads in sovereignty-driven contexts where isolation, controlled data handling, reliability, and auditability are mandatory.

Additional Information

What do we offer you?

Work environment & flexibility

• International, dynamic and collaborative environment.

• T-Social: social initiatives (sports, community, health, ...).

• Hybrid work model (remote/on-site).

• Flexible working hours.

Growth & development

• Customized training: access to Coursera to learn whatever you want, whenever you want.

• Weekly language classes (English & German).

• International Mentoring Sessions & Experience Days.

Compensation & benefits

• Flexible compensation plan (health insurance, meal vouchers, childcare, transport).

• Telemedicine.

• Life and accident insurance.

• Social fund.

Wellbeing & time off

• 26+ working days of vacation per year.

• Free access to specialists services (medical, legal, wellness).

• 100% salary coverage during medical leave.

• And many more advantages of being part of T-Systems!

If you are looking for a new challenge, do not hesitate to send us your CV! Please send CV in English. Join our team! T-Systems Iberia will only process the CVs of candidates who meet the requirements specified for each offer.

Your Task

This role focuses on building and operating Kubernetes environments that host AI engineering tools, internal model gateways, retrieval components, workflow services, CI/CD runners, and documentation services. You will implement GitOps and Infrastructure as Code patterns for reproducible provisioning, configuration, policy enforcement, platform upgrades, and disaster recovery readiness.

Key Responsibilities

• Build and operate Kubernetes environments that host AI engineering tools, internal model gateways, retrieval components, workflow services, CI/CD runners, and documentation services

• Implement GitOps and Infrastructure as Code patterns for reproducible provisioning, configuration, policy enforcement, platform upgrades, and disaster recovery readiness

• Manage private registries, package mirrors, secrets, identity integration, network segmentation, storage classes, backup routines, and controlled connectivity models

• Provide observability for engineering workloads, including metrics, logs, traces, GPU and CPU utilization, service health, cost signals, and operational runbooks

• Work with software, security, and architecture teams to ensure the platform supports AI-assisted SDLC workflows without creating uncontrolled data exposure or audit gaps

Platform Components and Tools

• You will work with platform tooling such as Kubernetes, Helm, Terraform, Ansible, ArgoCD, Crossplane, GitLab runners, Jenkins agents, private registries, and internal package mirrors.

• You will manage AI platform components such as vLLM, Ollama, OpenAI-compatible gateways, Qdrant or similar vector stores, Open WebUI, Continue-compatible endpoints, and workflow services.

• You will utilize observability and operations stacks such as Prometheus, Grafana, Loki, OpenTelemetry, ELK/OpenSearch, Alertmanager, SRE runbooks, and incident management tooling.

• You will implement security and governance components such as Vault, Keycloak, network policies, RBAC, admission controls, image scanning, SBOM tooling, and audit logging.

• You will maintain infrastructure awareness covering GPU-backed nodes, CPU-only fallback, storage performance, network isolation, proxy patterns, on-premise environments, and dedicated landing zones.

Your Profile

We are seeking a highly skilled Platform Engineer with extensive experience in Kubernetes, infrastructure automation, and AI platform operations. The ideal candidate will have deep expertise in building production-grade engineering platforms with strong focus on security, observability, and operational excellence in high-security, sovereignty-driven environments.

Must Have Skills

• 5+ years of experience in SRE, platform engineering, DevOps, cloud infrastructure, or operations roles

• Strong Kubernetes expertise

• Strong Linux expertise

• Proven experience building and operating production-grade engineering platforms

• Experience with GitOps practices and patterns

• Experience with Infrastructure as Code

• Experience implementing observability solutions

• Experience creating and maintaining operational runbooks

• Hands-on skills in Terraform

• Hands-on skills in Ansible

• Hands-on skills in Helm

• Hands-on skills in Python or shell scripting

• Experience with CI/CD runners

• Experience with private registries

• Experience with secure configuration management

• Good understanding of networking concepts and implementation

• Good understanding of storage systems and management

• Good understanding of secrets management

• Good understanding of access control mechanisms

• Good understanding of monitoring and observability

• Good understanding of backup and disaster recovery

• Good understanding of operational hardening in high-security environments

• Comfortable supporting AI-enabled engineering workloads in sovereignty-driven contexts

• Experience with isolation and controlled data handling requirements

• Experience ensuring reliability and auditability in secure environments