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 integral 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 a

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