Work with stakeholders across Compliance, Trading, Operations, Legal, Sales, and Finance to identify, scope, and prioritize use cases that genuinely move the needle.
Engineer production data solutions: Deterministic automations, AI agents, RAG systems over internal documents, structured extraction pipelines.
Build the firm's "innovation lab" environment where new use cases can be prototyped and evaluated.
Maintain prompt and skill libraries as reusable, version-controlled assets, not as one-off scripts.
Maintain the firm-wide inventory of AI systems and use cases, including those built outside D&A.
Run the operational side of the company’s AI approval process: documentation, risk classification, model cards, evaluation artifacts. Policy is set at the executive level; you make sure the operational practice meets it.
Conduct technical review of new AI initiatives proposed elsewhere in the company; advise on scope, risk, and design choices.
Contribute to ELT pipelines on the Dagster + SQLMesh + dlt stack, primarily where AI & automation use cases require new data sources or transformations.
Build the data substrate that AI workloads consume; feature views, document indexes, and structured event tables.
Maintain infrastructure as code in Git with proper review and deployment standards.

3–6 years of relevant experience. We are flexible on title, could be AI engineer, analytics engineer with AI focus, or data engineer who is pivoted to AI. What matters is shipped work.
Demonstrable production experience with LLM applications: at minimum structured extraction with LLMs, and agentic patterns (tool use, multi-step workflows). You can describe what failed and what you learned.
Strong Python; comfortable building production ready code, not just notebooks.
Working knowledge of evaluation discipline for LLM applications (eval sets, regression tests, observability), conceptual understanding of retrieval, and how to handle hallucination.
Familiarity with at least one orchestrator (Dagster, Airflow, Prefect) and one transformation framework (SQLMesh, dbt).
Solid SQL (window functions, joins, query design).
Cloud experience, ideally GCP and BigQuery.
Genuine curiosity about regulated environments and the discipline they require.
Professional proficiency in English (German is a plus).
Eligibility to work in Switzerland (Swiss permit or EU/EFTA citizenship).

Be part of an international, fast-paced blockchain and fintech team led by experienced professionals
Opportunity to travel and attend leading events
Shape the future of finance while working at the cutting edge of B2B digital asset solutions
Contribute to a collaborative, entrepreneurial culture with flat hierarchies
Take on meaningful responsibility with room for learning and professional growth
Gain deep industry insights and make a tangible impact
Join regular company-wide meetings, knowledge-sharing sessions, and team events
Enjoy a modern and central workplace in Zurich with top-tier infrastructure

AI Engineer

Key skills