Member of Technical Staff Intern - Germany

ERPs ran the physical world for half a century. Dryft is building the intelligence layer that will power the next.

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THE ROLE

As a Member of Technical Staff Intern , you'll build the system that decides how some of the largest manufacturers in the world operate. That means combining agent-based reasoning with mathematical optimization and simulation on large-scale industrial data.

• Build agents people trust – when an agent runs a factory's week, the largest industrial companies in the world have to trust it with their critical processes and understand every decision it makes; you build the routing, orchestration and guardrails behind that
• Ship features end-to-end – you understand the user need, and you get the freedom to build it across the LLM pipeline, infrastructure, backend and frontend, in production in your first weeks
• Work close to the users – sit with the planners who use it, see what would make their work 10x faster, and build it

You'll own your own features from day one, and what you ship decides what a plant does next week.

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YOU

• Full-stack shipper – you've shipped production code end-to-end, you build scalable backend and infra that handles massive amounts of structured and unstructured data, and you build the interface that makes it usable
• Highly technical – you've built something technically hard, and you can walk us through every decision behind it
• Product sense – you spot the feature hiding in a user's complaint, and you've deleted your own favorite one because nobody used it
• You care about getting it right – you know when it has to be 100% and when to keep it simple, and when it matters, you're still chasing the root cause at 2am
• Sense of urgency – you'd rather ship it tonight than sleep on an open PR
• Language – you're fully fluent in German and English
• Relocation – you're ready to work onsite in Munich (we support visa)

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TECH STACK

• FE (TypeScript): React, Chakra UI v3, TanStack Router, TanStack Query, Vite
• BE (Python): FastAPI with Pydantic v2, Temporal, Postgres with pgvector, dagster
• AI: Pydantic AI, Langfuse

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Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung