AI Engineer
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AI Engineer at Crypto Finance AG: Zürich, Швейцарія; Гібридно; Повна зайнятість; Старший спеціаліст; IT. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Zürich, Швейцарія, Гібридно
- Role classification: IT, Data Science та ML, Повна зайнятість, Старший спеціаліст
- Source freshness: checked by JobGrid on 2026-06-05.
- Application path: candidates continue to the employer application page with non-personal referral tags.
Crypto Finance Group, part of Deutsche Börse Group, provides professional digital asset solutions to institutional clients. The Group comprises Crypto Finance AG, regulated by FINMA in Switzerland, offering trading, custody, and wallet services, as well as Crypto Finance (Deutschland) GmbH, regulated by BaFin in Germany, offering trading and custody services. In January 2025, Crypto Finance secured a MiCAR license for the European market as one of the first providers in the EU. Crypto Finance AG is a SIX-approved crypto custodian for ETP issuers.
For more information, please visit our website at About us - Crypto Finance
We are currently looking for a AI Engineer. In the role, you will work closely with internal stakeholders, and the starting date is as soon as possible at our office on the 24th floor of the Prime Tower in Zurich
Responsibilities
AI & Automation Engineering
- 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.
AI Governance and Inventory
- 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.
Data Engineering and Platform
- 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.