Production AI and backend engineer based in Berlin.
I build Go/Python systems, LLM workflows, developer tools, and correctness-critical backend infrastructure. Most of my work sits where a demo has to become something real: observable, testable, scalable, and maintainable.
- Production AI features: LLM orchestration, agents, RAG, evals, tracing, and failure handling
- Backend systems: Go, Python, FastAPI, Django, PostgreSQL, Redis, queues, and APIs
- Infrastructure: AWS, Kubernetes, Terraform, Docker, and CI/CD
- Developer tools: CLIs, debugging dashboards, observability, and workflow automation
I build tools for developers working with backend systems and AI-assisted workflows.
- GoVisual - zero-config HTTP request visualizer for Go
- FastAPI Radar - real-time debugging dashboard for FastAPI
- LLMDog - package repositories into LLM-ready context
- PromptPilot - version, test, and optimize prompts
- K9Sight - TUI for debugging Kubernetes workloads
I help SaaS teams ship production AI and backend systems.
Best fit:
- You have an LLM or AI prototype that works in demos but needs production hardening
- You need evals, observability, fallbacks, or better architecture around an AI feature
- Your Go/Python backend is slow, unstable, or hard to change
- You need a senior technical partner for a focused 2-4 week sprint
Not a fit:
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Generic landing pages
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Small bug-fix tasks
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"Just wrap the OpenAI API" projects
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Work without a clear business problem
I write about production systems, AI features that survive real users, and engineering tradeoffs.
Previously co-founder and principal engineer at liftOS, where I built AI productivity systems, backend infrastructure, and cloud-native services. I have worked across fintech, SaaS, developer tools, and enterprise automation.
Stack I reach for most often:
Go | Python | TypeScript
FastAPI | Django | React | Node.js
PostgreSQL | Redis | Qdrant | Kafka
AWS | Kubernetes | Terraform | Docker
OpenAI | Anthropic | LangChain