Cloud & Platform Engineer with 15+ years in Enterprise IT — currently building an open specialization in Platform Engineering for AI workloads.

Current focus (builds in public on wesa.dev):

Making GenAI production-ready for Java/Spring enterprises in regulated industries. Specifically:

• LLM serving on Kubernetes (vLLM, LiteLLM, Triton)
• GPU scheduling — NVIDIA GPU Operator, Karpenter, MIG
• RAG infrastructure — Qdrant, embeddings, rerankers
• Multi-tenant cost tracking per token for LLM platforms
• GDPR-compliant self-hosting + practical EU AI Act application

Backing:

20+ cloud migration and DevOps transformation projects at 1&1, Deutsche Telekom, Deutsche Bahn, Lufthansa, and LR Health & Beauty. Up to 30% faster deployments and significant cost reductions in AWS and Kubernetes operations.

Why this combination:

Cloud-native + Enterprise Java + compliance is a rare mix in the German market. AI hype profiles lack Kubernetes. Cloud-native profiles lack Spring. I build both — production-ready, documented, without buzzwords.

Approach:

Instead of LinkedIn slides and architecture PowerPoints, I publish Helm charts, Terraform modules, and honest write-ups on wesa.dev. What works gets shown. What doesn't work gets documented just as openly.

If you want to integrate GenAI into your existing Java or cloud stack — GDPR-secure, self-hosted, or hybrid — let's talk.

→ wesa.dev
→ [email protected]