Founding Data Engineer, AI Platform for Enterprise

Dover

San Francisco (CA)

In loco

USD 180.000 - 240.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Descrizione del lavoro

Nth AI is building Nexus, an AI-native implementation platform that creates trusted data, semantic models, and governed business context for enterprise AI. You will design, code, test, and ship the software that automates data integration, transformation, modeling, and validation.

You will work directly with enterprise customers, understand their systems, deploy what you build, and turn challenges into reusable capabilities across deployments.

Competenze

  • Production software engineering ability.
  • Deep enterprise data engineering experience.
  • Fluency in the Microsoft data and AI ecosystem.
  • Enterprise customer experience.
  • Strong engineering judgment.

Mansioni

  • Design, code, test, and ship Nexus software for enterprise AI deployment.
  • Collaborate with customers to understand systems and requirements and deploy solutions.
  • Build backend services, APIs, and data integrations powering end-to-end implementation.
  • Develop automated data engineering capabilities and semantic models.
  • Ensure enterprise-ready deployments with authentication, monitoring and governance.
  • Translate customer needs into reusable platform capabilities.

Conoscenze

Production software engineering
Enterprise data engineering
Microsoft Fabric
Azure AI Foundry
Enterprise customer experience
Engineering judgment

Strumenti

Spark
PySpark
SQL

Descrizione del lavoro

Nth AI is building Nexus, an AI-native implementation platform that creates trusted data, semantic models, and governed business context for enterprise AI. You will design, code, test, and ship the software that automates data integration, transformation, modeling, and validation.

You will work directly with enterprise customers, understand their systems, deploy what you build, and turn challenges into reusable capabilities across deployments.

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