Senior AI Data Engineer — Knowledge Graphs & AWS

GE Aerospace; Charleston (WV); Remote; USD 110,000 - 145,000; Full time

Job summary

GE Aerospace is seeking a Senior Data Engineer to design the AWS-native data foundation behind enterprise AI apps, including knowledge graphs, semantic layers, and retrieval pipelines. You will set patterns for data access, curation, and extension across structured and unstructured sources.

You will lead data modeling, pipelines, and governance while collaborating with AI engineers and product teams. The role is remote in the United States with a competitive benefits package.

Qualifications

• Bachelor's degree in CS/Engineering or STEM field.
• A minimum of three years of data engineering experience.
• 5+ years of hands-on data engineering with data models and semantic layers (desired).
• Production experience with knowledge graphs and graph query languages.

Responsibilities

• Lead design and evolution of knowledge graphs and ontologies powering AI reasoning and retrieval.
• Align enterprise data into a coherent, provenance-rich graph across sources.
• Own retrieval substrate and improve grounding quality.
• Curate grounding corpora, eval datasets, and benchmarks for LLM features.
• Instrument metrics for retrieval quality and grounding accuracy; reduce regressions.
• Shape training and inference data contracts with AI engineers.
• Build data models and pipelines on AWS; use Glue, Lambda, S3, Athena, OpenSearch, Neptune.
• Author infrastructure as code via CloudFormation or CDK; enforce best practices.
• Profile sources, identify data quality gaps, and design automated validation.
• Collaborate with security for data access and policy integration.

Skills

Data modeling

Python

SQL

Cross-functional collaboration

Mentoring

Education

Bachelor's degree in Computer Science, Engineering, or a STEM field

Tools

AWS

CloudFormation/CDK

Glue

Lambda

Step Functions

S3

OpenSearch

Neptune

Bedrock

Job description

GE Aerospace is seeking a Senior Data Engineer to design the AWS-native data foundation behind enterprise AI apps, including knowledge graphs, semantic layers, and retrieval pipelines. You will set patterns for data access, curation, and extension across structured and unstructured sources.

You will lead data modeling, pipelines, and governance while collaborating with AI engineers and product teams. The role is remote in the United States with a competitive benefits package.