GenAI Engineer: Vertex AI Pipelines for Real-Time Insights

Equifax

Alpharetta (GA)

Hybrid

USD 130.000 - 190.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

Equifax seeks a Generative AI Engineer to design GenAI solutions on Google Cloud Vertex AI, building pipelines that turn data into actionable business insights. You’ll work with large data sources and collaborate with engineering teams to deploy robust AI capabilities.

The role emphasizes prompt engineering, RAG strategies, and integration into dashboards, APIs, and data pipelines while staying abreast of new AI research and industry standards.

Qualifikationen

  • Bachelor’s degree in a quantitative field or equivalent.
  • Hands-on experience building Generative AI or LLM-based solutions.
  • 1+ years in modern cloud environments.
  • Proficiency in Python and AI frameworks like LangChain.
  • Familiarity with REST APIs and lightweight web frameworks.

Aufgaben

  • Design GenAI components on Google Cloud Vertex AI to extract insights from data.
  • Integrate diverse data sources into AI/LLM solutions and deploy with engineering teams.
  • Apply prompt engineering and RAG strategies to improve accuracy.
  • Embed GenAI capabilities into data pipelines, dashboards and APIs for real-time analytics.
  • Translate business requests into AI-enabled analytical solutions.
  • Stay current with advances in Generative AI and its data analysis applications.
  • Communicate complex concepts clearly to technical and non-technical audiences.

Kenntnisse

Generative AI
LLM pipelines
Python
GCP Vertex AI
LangChain
REST APIs

Ausbildung

Bachelor’s degree in CS or related field

Tools

Vertex AI
BigQuery
Flask/FastAPI

Jobbeschreibung

Equifax seeks a Generative AI Engineer to design GenAI solutions on Google Cloud Vertex AI, building pipelines that turn data into actionable business insights. You’ll work with large data sources and collaborate with engineering teams to deploy robust AI capabilities.

The role emphasizes prompt engineering, RAG strategies, and integration into dashboards, APIs, and data pipelines while staying abreast of new AI research and industry standards.

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