AI Data Engineer

Skills
BusinessConnectorsDatabasesLarge Language ModelsMotorsOptimizationReadiness
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 5+ years in data engineering ETL development or database management
  • Strong experience building custom API connectors and data ingestion scripts
  • Experience integrating data with enterprise search engines AI agents or RAG-based systems
  • Practical experience preparing data for LLMs and agentic orchestration tools
  • Experience working with unstructured data and NLP concepts
  • Strong proficiency in SQL and Python

Nice to have

  • Attention to detail
  • Enterprise knowledge management
  • Data source auditing
  • Strong communication

Day to day

  • Ensure the AI agent ecosystem is powered by high-quality structured and retrieval-ready data.
  • Build and maintain custom connectors APIs and ETL pipelines to extract data from core business systems for AI tools.
  • Design optimize and manage data pipelines retrieval architectures and data freshness controls to support RAG performance and reduce hallucinations.
  • Create an AI Data Library map enterprise data sources and collaborate across teams to expose secure performant data to AI systems.
  • Implement automated data quality checks and governance controls including sensitive data handling and PII flagging.