We're hiring an Applied AI Engineer to own AI features end-to-end, build and evaluate LLM systems, and work with product to decide AI capabilities. Strong Python skills and German language proficiency required. €115k to €125k plus equity.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
I'm hiring an Applied AI Engineer for a Munich based scale-up. The product is live, customers are paying, and the AI features now drive most of the usage. They were built quickly and need to hold up at significantly higher volume.
The role
You own AI features end to end.
- Ship LLM systems into production: retrieval, tool use, multi-step agents, structured extraction.
- Build the evaluation layer. Golden datasets, regression tests in CI, offline scoring.
- Move features from 80% accuracy to 95%+ through error analysis, better context, guardrails and fallbacks.
- Instrument what you build. Traces, latency, cost per call, quality drift.
- Work with product early to decide what the AI should and shouldn't do.
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You'll need
- 3 to 5 years building software, with LLM systems live in production.
- Strong Python. Maintainable code, solid with APIs, queues and databases.
- A clear view on how to evaluate model output.
- Ability to debug across prompt, model, retrieval, data and infrastructure.
- German at native or C2 level. This is a hard requirement, the role is customer-facing and internal work is conducted in German.
- Fluent English alongside it.
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Bonus: agent frameworks, fine-tuning, AWS/GCP/Azure, or a backend background moved into AI.
Why this one
- Full ownership of an area rather than a slice of someone else's roadmap.
- Tune against real production traffic and real failure cases.
- Weekly releases. Feature flags and fast rollbacks.
- €115k to €125k plus equity.
- Visa sponsorship and relocation support available.
- Learning budget and your choice of equipment.
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Process
Four steps, completed within three weeks.
- 30 minutes with the hiring manager.
- Technical deep dive on a system you've built.
- Scoped practical task, paid if it runs over two hours.
- Team and founder conversation, then a decision.
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