Sovereign AI Platform Engineer T Cloud Public (mfd)

Mission
Design build and operate a sovereign AI toolchain used in isolated or tightly controlled environments including model serving retrieval orchestration observability and secure platform operations for enterprise AI engineering workloads

Role focus
This role centers on open-source or open-weight LLM stacks air-gapped or isolated deployment models Kubernetes-based platform engineering GPU-enabled environments and auditable AI operations suitable for sovereignty-sensitive programs

Key responsibilities

• Design and run Kubernetes environments optimized for AI inference retrieval experimentation and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks model gateways vector databases and supporting platform components
• Build reproducible platform automation using Infrastructure as Code and GitOps approaches for stable auditable delivery
• Manage local registries package mirrors secrets access controls storage networking and observability in environments with limited or no public cloud dependency.
• Optimize GPU compute and storage usage for reliable AI workloads while maintaining security and data sovereignty requirements

Examples of market tools models and platform components expected

• Inference and local serving stacks such as vLLM Ollama or OpenAI-compatible self-hosted endpoints.
• Open-source or open-weight models appropriate for sovereign deployment for example coding-capable and general-purpose families hosted internally through approved serving layers.
• Platform tooling such as Kubernetes Helm Terraform Ansible ArgoCD private registries Qdrant or similar vector stores and Open WebUI or comparable internal interfaces.
• Developer-facing integration options such as VS Code-compatible extensions Continue-style local model connectors or editor integrations pointed at internal APIs instead of external SaaS endpoints.
• Hardware awareness covering GPU-backed nodes CPU-only fallback options storage performance network isolation and on-prem or dedicated infrastructure patterns.

Qualifications :

• 5 years in platform engineering DevOps SRE or MLOps with strong Kubernetes and Linux expertise.
• Proven experience with AI infrastructure model serving private or on-prem deployments and production operations for LLM-based workloads.
• Strong hands-on skills in Python plus automation tooling such as Terraform Ansible Helm and GitOps workflows.
• Good understanding of networking storage access control monitoring and operational hardening in high-security environments.
• Comfortable working in sovereignty-driven environments where auditability isolation and controlled data handling 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 specialist 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.

Remote Work :

No

Employment Type :

Full-time