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AI Engineer(m/w/x)
Developing RAG systems and AI agents for crypto finance, with structured extraction pipelines. Production LLM application experience required. Travel opportunities, attendance at leading events.
Requirements
- 3-6 years relevant experience
- Production experience with LLM applications (structured extraction, agentic patterns)
- Strong Python for production code
- Working knowledge of LLM evaluation discipline
- Familiarity with orchestrator (Dagster, Airflow, Prefect)
- Familiarity with transformation framework (SQLMesh, dbt)
- Solid SQL (window functions, joins, query design)
- Cloud experience, ideally GCP and BigQuery
- Curiosity about regulated environments
- Eligibility to work in Switzerland
- Preference for simplest working solution (SQL before vector search)
- Ability to identify non-AI problems
- Ability to run stakeholder workshops and write production code
- Serious approach to documentation, evaluation, audit trails
- Prior exposure to regulated financial services or crypto
- Not a prompt engineer with no production experience
- Not a pure data engineer pivoting to AI without prior LLM work
- Not a strategist or generalist AI enthusiast
Tasks
- Collaborate with stakeholders to identify and prioritize use cases
- Engineer production data solutions and AI agents
- Develop RAG systems over internal documents
- Create structured extraction pipelines
- Prototype and evaluate new use cases in the innovation lab
- Maintain prompt and skill libraries as version-controlled assets
- Manage the firm-wide inventory of AI systems and use cases
- Document and classify risks for AI systems
- Create model cards and evaluation artifacts
- Ensure operational practices meet executive policies
- Conduct technical reviews of new AI initiatives
- Advise on scope, risk, and design choices for AI projects
- Contribute to ELT pipelines using Dagster, SQLMesh, and dlt
- Build data substrates for AI workloads
- Create feature views, document indexes, and structured event tables
- Maintain infrastructure as code in Git with review and deployment standards
Work Experience
- 3 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
- German – is a plus
Tools & Technologies
- Python
- LLM
- Dagster
- Airflow
- Prefect
- SQLMesh
- dbt
- SQL
- GCP
- BigQuery
Benefits
Other Benefits
- Opportunity to travel
- Deep industry insights
- Central workplace
- Experienced professionals
Learning & Development
- Attend leading events
- Room for learning
- Knowledge-sharing sessions
Informal Culture
- Collaborative culture
- Flat hierarchies
- Regular company-wide meetings
- International team
Startup Environment
- Entrepreneurial culture
- Fast-paced team
Purpose-Driven Work
- Meaningful responsibility
- Tangible impact
Career Advancement
- Professional growth
Team Events
- Team events
Modern Office
- Modern workplace
Modern Equipment
- Top-tier infrastructure
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AI Engineer(m/w/x)
Developing RAG systems and AI agents for crypto finance, with structured extraction pipelines. Production LLM application experience required. Travel opportunities, attendance at leading events.
Requirements
- 3-6 years relevant experience
- Production experience with LLM applications (structured extraction, agentic patterns)
- Strong Python for production code
- Working knowledge of LLM evaluation discipline
- Familiarity with orchestrator (Dagster, Airflow, Prefect)
- Familiarity with transformation framework (SQLMesh, dbt)
- Solid SQL (window functions, joins, query design)
- Cloud experience, ideally GCP and BigQuery
- Curiosity about regulated environments
- Eligibility to work in Switzerland
- Preference for simplest working solution (SQL before vector search)
- Ability to identify non-AI problems
- Ability to run stakeholder workshops and write production code
- Serious approach to documentation, evaluation, audit trails
- Prior exposure to regulated financial services or crypto
- Not a prompt engineer with no production experience
- Not a pure data engineer pivoting to AI without prior LLM work
- Not a strategist or generalist AI enthusiast
Tasks
- Collaborate with stakeholders to identify and prioritize use cases
- Engineer production data solutions and AI agents
- Develop RAG systems over internal documents
- Create structured extraction pipelines
- Prototype and evaluate new use cases in the innovation lab
- Maintain prompt and skill libraries as version-controlled assets
- Manage the firm-wide inventory of AI systems and use cases
- Document and classify risks for AI systems
- Create model cards and evaluation artifacts
- Ensure operational practices meet executive policies
- Conduct technical reviews of new AI initiatives
- Advise on scope, risk, and design choices for AI projects
- Contribute to ELT pipelines using Dagster, SQLMesh, and dlt
- Build data substrates for AI workloads
- Create feature views, document indexes, and structured event tables
- Maintain infrastructure as code in Git with review and deployment standards
Work Experience
- 3 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
- German – is a plus
Tools & Technologies
- Python
- LLM
- Dagster
- Airflow
- Prefect
- SQLMesh
- dbt
- SQL
- GCP
- BigQuery
Benefits
Other Benefits
- Opportunity to travel
- Deep industry insights
- Central workplace
- Experienced professionals
Learning & Development
- Attend leading events
- Room for learning
- Knowledge-sharing sessions
Informal Culture
- Collaborative culture
- Flat hierarchies
- Regular company-wide meetings
- International team
Startup Environment
- Entrepreneurial culture
- Fast-paced team
Purpose-Driven Work
- Meaningful responsibility
- Tangible impact
Career Advancement
- Professional growth
Team Events
- Team events
Modern Office
- Modern workplace
Modern Equipment
- Top-tier infrastructure
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Crypto Finance AG
Industry
FinancialServices
Description
Crypto Finance Group, part of Deutsche Börse Group, provides professional digital asset solutions to institutional clients, including trading, custody, and wallet services.
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