11 hours ago
Berlin, GermanyMid Level
Responsibilities
- Own AI automation use cases from customer discovery through production deployment.
- Turn ambiguous enterprise problems into scoped, buildable solutions and ship them quickly.
- Build applied AI solutions using LLMs, agentic workflows, vision models, embeddings, and heuristics.
- Design and implement data pipelines for document ingestion, extraction, validation, and orchestration.
- Identify recurring patterns and codify them into reusable templates.
- Work directly with enterprise stakeholders, including on-site customer visits, to gather requirements and explain technical trade-offs.
- Help shape the technical direction of the product and company.
Requirements
- At least 2 years of experience as a software engineer or data scientist building production systems.
- Strong computer science fundamentals from a degree or clearly equivalent formal grounding.
- Hands-on experience deploying LLMs, agentic workflows, vision models, and embeddings in production.
- Full-stack capability with backend API development in Node.js/TypeScript or Python and frontend development in TypeScript/React or similar.
- Experience designing data pipelines for document processing, extraction, and validation involving unstructured PDFs and images.
- Experience integrating multiple LLM providers such as OpenAI, Azure, Gemini, and Cohere, plus solid prompt-engineering skills.
- Familiarity with vector databases, semantic search, or knowledge graphs is preferred.
- B2B experience, ideally in a customer-facing or technical customer-success role, is preferred.
- Early-stage startup or founding-team experience and comfort with ambiguity and rapid iteration are preferred.
- C1-level German or above is essential for working with German enterprise stakeholders.
- Pragmatic, action-oriented interest in applied AI over theory.
Benefits
- Salary range of 72,000 to 100,000 EUR annually.
- On-site work five days per week in Berlin, Germany.
- Occasional travel to customer sites across the region.
Tech Stack
Categories
Forward Deployed
