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AI Data Engineer
Skills
BusinessConnectorsDatabasesLarge Language ModelsMotorsOptimizationReadiness
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.