AI Engineer

• 11 September 2026
• 100%
• Indefinite duration
• Zürich

Join our Data & Analytics team at Crypto Finance, headquartered in the Prime Tower in Zurich. Your main mission is to advance the company's AI strategy: identifying use cases across different departments, designing production-ready AI and automation solutions, and contributing to the implementation of the company's AI governance. You will also participate in the data platform that supports Finance, Operations, and Risk reporting, as AI work in our company relies directly on this platform.

This is a hybrid role for a person who is equally comfortable in a workshop with stakeholders as in an IDE. The work may cover AI agents and copilots, deterministic automation, RAG systems, as well as the data infrastructure they rely on. You will need to reject bad use cases as much as deliver good results.

What you will do:

AI Engineering & Automation

• Collaborate with stakeholders from the Compliance, Trading, Operations, Legal, Sales, and Finance departments to identify, define, and prioritize use cases that have a real impact.
• Design production data solutions: deterministic automations, AI agents, RAG systems on internal documents, structured extraction pipelines.
• Build the company's "innovation laboratory" environment where new use cases can be prototyped and evaluated.
• Maintain prompt and skill libraries as reusable and versioned assets, rather than one-off scripts.

AI Governance and Inventory

• Maintain the global inventory of the company's AI systems and use cases, including those developed outside of D&A.
• Manage the operational aspect of the company's AI approval process: documentation, risk classification, template sheets, evaluation artifacts. Policy is defined at the executive level; you ensure that operational practice respects it.
• Perform technical reviews of new AI initiatives proposed elsewhere in the company; advise on scope, risks, and design choices.

Data Engineering and Platform

• Contribute to ELT pipelines on the Dagster + SQLMesh + dlt stack, primarily when AI & automation use cases require new data sources or transformations.
• Build the data substrate consumed by AI workloads; feature views, document indices, and structured event tables.
• Maintain infrastructure as code in Git with appropriate review and deployment standards.
• 3 to 6 years of relevant experience. We are flexible on the title; it can be AI engineer, analytics engineer with an AI focus, or data engineer pivoted towards AI. What matters is the work delivered.
• Demonstrable production experience with LLM applications: at minimum structured extraction with LLM, and agentic models (tool use, multi-step workflows). You can explain what failed and what you learned from it.
• Solid mastery of Python; comfortable producing production-ready code, not just notebooks.
• Practical knowledge of the evaluation discipline for LLM applications (evaluation sets, regression tests, observability), conceptual understanding of information retrieval and hallucination management.
• Familiarity with at least one orchestrator (Dagster, Airflow, Prefect) and one transformation framework (SQLMesh, dbt).
• Strong mastery of SQL (window functions, joins, query design).
• Cloud experience, ideally GCP and BigQuery.
• Sincere curiosity for regulated environments and the rigor they require.
• Professional mastery of English (German is a plus).
• Eligibility to work in Switzerland (Swiss permit or EU/EFTA citizenship).

What is also important is your way of thinking:

• You opt for the simplest solution that works. Basic SQL before vector search. Rules before agents. You can explain why.
• You are comfortable saying "this is not an AI problem" when the right answer is a dashboard, a process correction, or a deterministic script.
• You can facilitate a workshop with stakeholders and write production code in the same week.
• You take documentation, evaluation, and audit trails seriously, not as an administrative burden.

Assets:

• Previous experience in regulated financial services, crypto, or comparable model risk environments.

What we are not looking for:

• "Prompt engineers" without production experience.
• Pure data engineers using this offer to pivot to AI without previous experience with LLMs.
• Generalist strategists or "AI enthusiasts." This is a builder role.
• Be part of an international, dynamic, blockchain and fintech team led by experienced professionals
• Shape the future of finance by working at the cutting edge of B2B digital asset solutions
• Contribute to a collaborative and entrepreneurial culture with flat hierarchies
• Take on significant responsibilities with opportunities for learning and professional development
• Gain deep industry knowledge and have a tangible impact
• Participate in regular company meetings, knowledge sharing sessions, and team events
• Enjoy a modern and central workplace in Zurich with first-class infrastructure

Our culture

At the heart of our company, we prioritize:

• Innovation and continuous learning
• Collaboration and pa