Business Analyst / AI Engineer

Responsibilities

• Make AI use cases work where it matters: in the day‑to‑day reality of complex industrial risk.
• Work as part of a cross‑functional delivery team responsible for AI use cases in Industrial Underwriting and Claims across their full lifecycle— from initial discovery and hypothesis work through experiment design, measurement, and operational adoption.
• Define ‘golden truth’ datasets, validate AI outputs against real underwriting and claims decisions, and ensure the business perspective is reflected in every model iteration.
• Understand and take responsibility for Prompts and RAG specifications for GenAI agents in underwriting and claims processes; design, test, and iterate them independently.
• Translate business rules, edge cases and compliance requirements (regulatory, legal, internal, including the EU AI Act) into structured, sprint‑ready specifications for the AI delivery team and support the AI use‑case lead in backlog management and prioritisation.
• Own business‑layer UAT: challenge model outputs against operational reality, run lateral validation loops with domain experts, and document failures with clear business impact.
• Track and drive AI adoption by running impact dashboards and building change materials that help underwriters and claims handlers to actually use the new tools.
• Represent the underwriting and claims business perspective in technical workshops, working directly with Data Scientists and the engineering team to shape solutions.

Profile

• Several years of work experience in the regulated industry, ideally insurance, with real operational depth in Industrial Insurance (knowledge of submission workflows, coverage logic and claims triage).
• At least 2 years of solid knowledge of GenAI prompting, agentic workflow design and model risk assessment, including explainability; able to build, evaluate and iterate LLM prompts and RAG retrieval logic for insurance documents.
• Track record of BA artefacts (BPMN process maps, edge‑case registers, acceptance criteria, user stories) that are delivery‑ready and grounded in structured analysis methodologies such as IIBA, IREB, CARS or comparable.
• Trained and experienced in problem structuring and solving, with structured thinking and planning based on project management skills like Six Sigma, Prince2 or comparable.
• Ability to translate EU AI Act obligations, regulatory and internal compliance requirements into workable design constraints for cloud‑based GenAI platforms, or willingness to dive into those details.
• International project experience; fluent in English (C2) and German (at least B2); comfortable presenting and debating at all levels, including C‑Level.
• Thrives under time pressure and in a high‑pace environment.

Benefits

Flexible working hours: flexitime arrangements and flexible working time models to suit your work‑life balance.

Health management: preventive measures, a wide variety of sports and various partnerships to keep you healthy.

Mobile working: up to 60 % mobile remote working model offers freedom and independence.

Further training: satisfaction of your thirst for knowledge with further training, subject‑specific seminars or work and study programmes.