AI Engineer: Production AI, Governance & Data Platform

Crypto-Finance-Ag

Zürich

Hybrid

CHF 120.000 - 170.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden
Bewerbungsgenerator

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Benefits dieser Stelle

Hybrid work model

Zusammenfassung

Crypto Finance, headquartered in the Prime Tower, Zurich, seeks a Data & Analytics professional to advance our AI strategy. You will identify use cases, engineer production-grade AI and automation solutions, and help build AI governance.

The role spans data platforms used by Finance, Operations and Risk and requires hands-on coding and stakeholder collaboration. You will push back on non-viable ideas while shipping robust, scalable AI.

Qualifikationen

  • 5+ years of production experience in AI or data engineering with LLMs.
  • Strong Python skills; able to ship production-grade code.
  • Experience with evaluation, observability, and handling model risk.
  • Familiar with orchestration and transformation frameworks (Dagster, Airflow, SQLMesh, dbt).
  • Solid SQL skills and cloud experience (GCP/BigQuery).
  • Excellent English; German a plus; eligibility to work in Switzerland.

Aufgaben

  • Identify and scope high-impact AI and automation use cases across departments.
  • Engineer production-grade AI/data solutions and deterministic automations.
  • Build an internal innovation lab to prototype and evaluate ideas.
  • Maintain AI governance artifacts, risk classifications, and model cards.
  • Contribute to ELT pipelines and data substrates over the Dagster/SQLMesh/dlt stack.
  • Collaborate with Compliance, Trading, Operations, Legal, Sales, and Finance.

Kenntnisse

Python
LLM applications
SQL
English

Tools

Dagster
SQLMesh
dbt
Airflow
BigQuery
GCP

Jobbeschreibung

Crypto Finance, headquartered in the Prime Tower, Zurich, seeks a Data & Analytics professional to advance our AI strategy. You will identify use cases, engineer production-grade AI and automation solutions, and help build AI governance.

The role spans data platforms used by Finance, Operations and Risk and requires hands-on coding and stakeholder collaboration. You will push back on non-viable ideas while shipping robust, scalable AI.

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