Senior AI Engineer (m/f/d)

Artefact · Berlin, Berlin; Hamburg, Hamburg; München, Bavariasenior

In short

▸Ingeniero de IA senior que lleva proyectos de IA de ideas a producción en entornos empresariales.
▸Trabajas con LLMs, RAG, vectores, prompt engineering y herramientas modernas como LangChain y Hugging Face en proyectos reales.
▸Destacan proyectos multiindustria con impacto real y colaboración estrecha con clientes y equipos interdisciplinarios.

Business-fluent English and German (both written and spoken) are mandatory

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What they ask for

✓3+ años de experiencia en ingeniería de IA o ML con proyectos en producción.
✓Título en ciencias de la computación, IA o campo afín.
✓Dominio de Python y servicios de nube (GCP, AWS o Azure).
✓Experiencia práctica con LLMs, prompt engineering, fine-tuning y RAG.
✓Conocimiento en DevOps/ML-Ops (Docker, Kubernetes, CI/CD).
✓Inglés y alemán fluentes (escrito y hablado) para trabajar en clientes y presentaciones.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonGCPAWSAzureLangChainPydanticAIMCP serversRAGFAISSWeaviate

Who should you write to at Artefact?

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Artefact , a global AI and data consulting company with rapid growth, is looking for a creative and tech-savvy Senior AI Engineer (m/f/d) to join the tech team full-time. Ideally, you are located in Hamburg, Munich, Berlin or nearby - but if you're based elsewhere in Germany and a great fit, we would still love to hear from you. Could this be you? Our data & AI experts develop production-ready, scalable solutions that bring real business value to our clients. You’ll work in interdisciplinary teams of data scientists, engineers, analysts and consultants to shape the future of data- and AI-driven products. Your responsibilities: Innovate. You’ll help identify business needs, explore data and AI use cases, and drive projects from idea to production - whether it’s a proof-of-concept or a scalable solution. Build. You’ll own your work end-to-end - from concept and architecture to implementation, optimization, and delivery. You design smart, robust solutions using data or LLMs and other AI technologies. Train. You’ll stay ahead of the curve - experimenting with new models, prompt engineering, fine-tuning, and tools. You’ll also share your knowledge within the team and benefit from our partners’ training offers (Google, AWS, etc.). Collaborate. You’ll work closely with clients, product owners, and non-technical stakeholders, balancing technical excellence with practical business impact. Gain broad experience: • Work on 1-3 projects per year across different industries and use cases - from customer service automation to knowledge management and internal tools. • Build real-world data and AI applications using modern tools like LangChain, PydanticAI, MCP servers, RAG pipelines, vector databases (e.g. FAISS, Weaviate), LlamaIndex, Vertex AI, OpenAI APIs, and Hugging Face models. • Shape the way clients use data and AI, driving innovation and best practices in production environments. Your mindset: • Curious & forward-thinking. You are passionate about solving complex problems using cutting-edge AI and data technologies. • Hands-on. You have experience with LLMs (e.g. OpenAI, Claude, Gemini, LLaMA), prompt engineering, API integration, and ML frameworks. • Holistic. You understand the full ML lifecycle, including data preparation, model deployment, evaluation, and monitoring. • Communicative. You can break down technical concepts for diverse audiences in English and ideally in German as well. • Supportive. You coach junior team members, provide constructive feedback, and actively contribute to our culture of learning. Profile: • Degree in computer science, AI, data science or similar field. • Experience: 3+ years of experience in machine learning or AI engineering, with hands-on AI projects in production. • Proficiency in Python and cloud-based AI services (GCP, AWS, or Azure). • Solid understanding of data analysis/engineering and AI-specific components like RAG, prompt design, fine-tuning, embeddings, and model evaluation. • Familiar with DevOps and ML-Ops best practices (Docker, Kubernetes, CI/CD). • Strong problem-solving skills, a sense of ownership, and a structured approach to work. • Languages : Business-fluent German and English (both written and spoken) are mandatory to participate in client workshops and deliver polished presentations. • Work Eligibility : A valid work

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