AI Engineer
Crypto Finance Group helps financial institutions access digital assets through regulated trading, custody, and staking services across Europe.
Funding history
Projects
About Crypto Finance Group
Crypto Finance Group helps financial institutions enter the digital asset space through regulated infrastructure and services. Users can trade digital assets 24/7, store assets securely in custody, and generate staking rewards. The group operates under FINMA regulation in Switzerland and BaFin regulation in Germany, providing trusted access to digital assets for institutional clients. Following its acquisition by Deutsche Börse Group in 2021, it expanded its European presence with MiCAR licensing.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will identify and prioritize AI and automation use cases with business stakeholders. You will build production-grade AI agents, RAG systems, structured extraction pipelines, and deterministic automations. You will maintain AI governance artifacts, review proposed initiatives, and contribute to data pipelines and infrastructure that support AI workloads.
Requirements
- 3–6 years of relevant experience
- Production experience with LLM applications, including structured extraction and agentic patterns
- Python
- LLM evaluation, regression testing, observability, retrieval, and hallucination handling
- An orchestrator such as Dagster, Airflow, or Prefect
- A transformation framework such as SQLMesh or dbt
- SQL
- Cloud experience, ideally GCP and BigQuery
- Professional proficiency in English
- Eligibility to work in Switzerland
Responsibilities
- Identify, scope, and prioritize AI and automation use cases with stakeholders
- Build deterministic automations, AI agents, RAG systems, and structured extraction pipelines
- Build and evaluate prototypes in an innovation-lab environment
- Maintain reusable version-controlled prompt and skill libraries
- Maintain the inventory of AI systems and use cases
- Run AI approval-process documentation, risk classification, model cards, and evaluation artifacts
- Review new AI initiatives and advise on scope, risk, and design
- Contribute to ELT pipelines using Dagster, SQLMesh, and dlt
- Build feature views, document indexes, and structured event tables
- Maintain infrastructure as code in Git
Benefits
- Regular company-wide meetings, knowledge-sharing sessions, and team events
- Modern central workplace in Zurich with top-tier infrastructure
