Wealth AI Engineer & Data Scientist (Zurich)

Union Bancaire Privée

Zürich

Hybrid

CHF 120,000 - 170,000

Full time

12 hours ago

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Job summary

Union Bancaire Privée (UBP) is seeking a Wealth Management AI Data Scientist / Engineer to turn business problems into scalable AI-enabled solutions within the WM Client Lifecycle AI & Reporting Team. You will work across AI, software engineering, data and business processes to deliver practical tools that support onboarding, KYC, transaction monitoring, and client insights.

This role blends architecture, prototyping and production-ready development in a regulated banking environment, with close

Qualifications

Master's degree in Computer Science, AI, Software Engineering or closely related discipline.
3+ years of relevant professional experience in AI engineering, software engineering or applied AI development.
Proven experience building real applications, products or production-quality prototypes.
Hands-on experience integrating LLMs or Generative AI into applications.
Experience developing backend services and working with modern application architectures.
Experience developing web-based user interfaces is a strong plus.
Familiarity with RAG, vector databases, knowledge graphs, graph databases or semantic search is an advantage.
Experience with client due diligence, client lifecycle processes or document-heavy workflows is beneficial.
Ability to translate business problems into technical solutions, with sound product thinking and an understanding of technical architecture and implementation.
Fluency in English; French or German is an advantage.
Strong analytical and problem-solving skills, intellectual curiosity, and excellent research, communication and presentation skills.

Responsibilities

Turn ambiguous business problems into clear technical solutions.
Design and build AI-enabled applications from concept through to implementation.
Integrate Large Language Models into real business workflows using RAG, prompting, tool use and agentic workflows.
Build backend services and APIs that connect AI applications with internal systems and data sources.
Develop or contribute to user-facing web applications that make AI capabilities simple and intuitive to use.
Work with structured and unstructured information, including documents and workflow data.
Build data-processing pipelines that prepare and organise information for AI applications.
Test solutions with real users and iterate based on feedback.
Ensure solutions are traceable, maintainable and compliant with regulations.
Take end-to-end ownership of technical delivery and explain choices to non-technical stakeholders.