Founding Ai Engineer
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Most AI agents never leave the demo. These ones run live inside real operations every day, reading inboxes, handling phone calls, and taking action across ERP, TMS and EDI systems for logistics companies across DACH. When they get something wrong, a real business feels it.
A funded, founder-led AI startup in Munich is hiring its Founding AI Engineer to own the layer that makes that work: the models, the evaluations, the observability, and the platform the rest of the engineering team builds on.
What you’ll own
- The AI infrastructure behind the product: choosing, testing, fine-tuning and deploying models, including open-source, and deciding when to switch
- Evaluations and trace analysis across agents and sessions, so every model change, prompt update or architecture shift is measured, not guessed
- Reliability in production: guardrails, retries, fallbacks, state and context management, and human escalation when the agent shouldn’t decide alone
- Cost, latency and accuracy, balanced deliberately rather than by accident
- Agent architecture and the core platform across backend services, integrations, data and event queues
- Technical direction alongside the founders, plus a real hand in hiring and shaping the engineering team as it grows
This is hands-on. You write production code daily. It’s not a research role, and it’s not an architecture role where you stop building.
What you bring
- 1.5 to 2+ years running LLM systems in production with real users, where you watched live traces and fixed what broke
- Strong grasp of agents, tool use, structured outputs and context engineering
- Hands‑on experience with observability and tracing tools such as Langfuse or LangSmith
- Solid engineering fundamentals: Python, TypeScript, SQL, APIs, data modelling and system design
- Comfort with asynchronous systems: queues, retries, idempotency, background jobs, failure handling
- Docker, CI/CD, cloud infrastructure and production debugging
- You follow model releases and research closely and turn them into decisions, not just opinions
Bonus: enterprise integrations, voice, email automation, or any logistics or supply chain exposure.
Who thrives here
You take ownership of messy, important problems without waiting for a spec. You ship the simple version first and know when it needs rebuilding properly. You build with AI tools as the default way you work. You’re direct, low ego, and happy to be close to customers and production incidents.
The setup
- Munich office, in person, five days. Not remote, and not a 9 to 5
- Small founding team working directly with the founders
- A fast process: one conversation, one hands‑on technical session building with an AI assistant, one founder conversation. Decision within a week