AI Engineer (m/f/d) - Healthcare IT

Responsibilities

• Own the evaluation harness. Build and maintain offline eval datasets, combine LLM-as-judge with deterministic checks, and wire regression gates into CI so quality is enforced before release - not discovered in production.
• Design and optimise RAG. Build retrieval pipelines over structured and unstructured clinical text: chunking, embedding and retrieval strategy, reranking, and grounded/cited generation. Measure retrieval quality (faithfulness, context relevance, recall), not just end-output vibes.
• Instrument and observe in production. Enable tracing every step an agent takes - LLM calls, tool calls, retrieval steps - monitor for quality drift, and close the loop by turning production failures into new eval cases.
• Optimise cost and latency. Treat cost-per-task as a first-class metric. Apply model routing/selection, caching, token budgeting, batching, and prompt efficiency.
• Essential Requirements
• Demonstrated, shipped production AI systems (preferably LLM/agent systems) - real systems that ran in front of real users, not notebooks or proofs-of-concept. Be ready to walk us through one, including how it failed and what you did about it.
• Strong software engineering fundamentals: Python, API design, automated testing, version control, containerisation.
• Hands-on agent orchestration with at least one framework and a clear understanding of how agentic systems break in production.
• Practical RAG experience: embeddings and vector stores, retrieval design, and retrieval-specific evaluation.
• LLM evaluation experience: building or operating eval harnesses and observability/tracing tooling.
• Comfort with ambiguity and unstructured problems, plus clear communication - able to explain technical trade-offs to clinical and product stakeholders.
• A degree in computer science, software engineering, or a related field.
• Proficiency in English and German language.
• Note on experience: we are looking for years of strong software engineering plus recent, hands-on agent work . Agent engineering is a young discipline, and we are not expecting a long tenure in it.
• Desirable Requirements
• Healthcare/clinical-software and data exposure.
• Strong foundation in statistics and probability theory.
• Awareness of MDR and EU AI Act implications for clinical AI (high-risk classification, human oversight, data governance, post-market monitoring).
• Deep cloud platform knowledge (especially AWS) and infrastructure-as-code.
• Model adaptation or fine-tuning.
• Familiarity with guardrail and safety frameworks for LLM applications.
• Proficiency in Italian language.

Benefits

Additional Information

Do you want a job with a purpose? And do you want to make healthcare safer, better and more reliable? Join our Team! Join us as our AI Engineer (m/f/d) - Healthcare IT at Dedalus , one of the World's leading healthcare technology companies, in Graz (Partially Remote/ Hybrid work) to do the best work of your career and make a profound impact in providing better care for a healthier planet. You will contribute to the engineering behind our agentic AI roadmap: designing, building, configuring, evaluating, and operating production-ready agents that work reliably and safely in a regulated healthcare environment. This is an application- and systems-layer engineering role. Your success is measured by delivering agents that survive contact with real users and real clinical workflows. You will work closely with clinical, product, and domain experts, but your core craft is shipping and qualifying agentic systems, building the evaluation infrastructure, and optimizing the cost and latency of running them at scale.

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