T-Systems is a global leader in information technology and digital transformation services, operating as the enterprise IT subsidiary of Deutsche Telekom. The company provides a wide range of integrated solutions, including cloud services, cybersecurity, digital connectivity, and industry-specific software, particularly for the healthcare, public sector, and manufacturing industries. With a global workforce of approximately 27,000 employees, it serves multinational corporations and public institutions worldwide.

In Spain, T-Systems Iberia is one of the country's largest IT employers, maintaining a significant presence in major technology hubs like Barcelona, Madrid, and Granada. The company is known for its multicultural environment and its role as a strategic partner for both the Spanish public administration and the private sector. For international professionals, T-Systems offers a stable environment with opportunities to work on large-scale digital transformation projects, often utilizing English as a primary language for international accounts and cloud-native technologies.

T-Systems was founded in 2000 as the IT services arm of Deutsche Telekom following the acquisition of debis Systemhaus. It has evolved from a traditional infrastructure provider into a global leader in digital services and multi-cloud management.

For international professionals

Operates major delivery centers across Spain, including a significant innovation hub in Granada and large offices in Barcelona and Madrid.
Offers flexible work models and 'Work from Anywhere' policies for many technical and consultancy roles within the Spanish territory.
Provides extensive internal training and certification paths for high-demand technologies including SAP, AWS, Azure, and Google Cloud.
Frequently recruits for international projects where English is the primary working language, facilitating the integration of non-Spanish speakers.
Strongly involved in the digitalization of the Spanish healthcare system and public administration, offering high-impact career opportunities.

Sovereign AI Platform Engineer T Cloud Public (m/f/d)

T-Systems Iberia

Requirements

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.

Benefits

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.

Original Advert

Company Description

T‑Systems is part of the Deutsche Telekom Group, with around 30.000 employees worldwide. We create technology with purpose to generate a positive impact on society. We are looking for curious talent, eager to learn, take on challenges, and contribute ideas that transform our customers' experience.

We trust people: we offer autonomy, continuous support, and a collaborative environment where you can grow without limits. We are one global team, guided by respect, integrity, and a passion for doing better every day.

Job Description

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, llama.cpp, 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.