Senior AI Engineer
Role details
Job location
Tech stack
Job description
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.
Requirements
- 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 permit for Germany.
Benefits & conditions
Pulled from the full job description
- Flexible schedule