Senior GenAI Data Scientist (m/f/d)

Experience building agentic GenAI systems in production (e.g., LangChain, AutoGen, Atomic Agents, or similar frameworks).

Strong coding skills in Python and experience with robust software engineering practices.

Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.

Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift).

Experience deploying AI systems in a cloud environment and working with modern ML stacks.

Familiarity with MLOps, prompt engineering, or LLM-based application design.

Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.

Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.

Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination.

Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns.

Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.

Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions.