Platform engineering01
Make the right path the easiest path.
Kubernetes foundations, GitOps delivery, policy boundaries and developer-facing infrastructure primitives.
Senior Infrastructure Engineer · Germany
Infrastructure
that runs itself.
Cloud-native platforms, governed AI infrastructure and resilient systems — designed to stay calm when production gets loud.
01
Engineering principle
Complexity belongs behind the interface.
The platform can be sophisticated underneath. The experience should still feel calm, legible and predictable — for developers, operators and the business.
AI infrastructure02
Govern every request, not just the model.
Routing, identity, MCP policy, inference, observability and cost evidence as one execution plane.
Reliability systems03
Recovery should be proved, not assumed.
Backups, automated restores, verification loops and bounded self-healing built around evidence.
02
Selected systems
Six repositories. Six different kinds of proof.
Top public systems on GitHub — the ones that best explain how the platform thinking lands in code.
01 / Architecture Rehearsal
Test the architecture
before production does.
Deterministic failure rehearsal for architectural assumptions, policy gates and evidence chains.
View case ↗REHEARSAL / 04approved
architectural risk
0.08
02 / TwinOps Control Plane
Treat industrial twins
like infrastructure.
GitOps control plane for industrial digital twins — compose, detect drift, reconcile, replay incidents.
View case ↗TWINOPS / CONTROLsynced
kit streamlive
gitopssynced
03 / AI Runtime Platform
Every AI request
passes through policy.
OpenAI-compatible gateway, MCP governance, KServe/vLLM, KEDA, OIDC, Redis and OpenTelemetry.
View case ↗AI RUNTIME / GATEpolicy on
identityoidc
latency4ms
verdictallow
ai-infra-control-plane
Policy, identity, audit, intent, MCP, FinOps and SLOs as one operating model.
View case ↗self-healing-infrastructure-chaos-engineering
Failure injection, bounded remediation loops and chaos-driven platform validation.
View case ↗gitops-duel-argocd-vs-flux
Interactive Argo CD vs Flux duel for drift, reconciliation and delivery tradeoffs.
View case ↗Recognition
Cloud Native Rockstars 2026
Professional recognition is useful when it points back to real systems, real constraints and work that holds up under scrutiny.
Open proof page ↗
Available for meaningful infrastructure conversations