Sovereign AI Platform Engineer (DevOps Engineer) (m/f/d)

Odmeňovanie

• From 2 100 EUR/month
• Final salary is negotiable.
• We are offering base salary depending on seniority level and previous experience of candidate. In addition to base salary we provide variable part and other financial benefits.
• 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

Remote work

Full-time

Náplň práce

• 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.

Technológie a platformové komponenty

• 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.

Požiadavky

• 5+ years in platform engineering, DevOps, SRE, or MLOps, with strong Kubernetes and Linux expertise.