Sr AI Data Engineer

General Electric Company

$110K — $145K *
US-AnywhereRemote in United States
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a STEM field
  • Minimum of three years of data engineering experience
  • 5+ years of hands-on data engineering with a focus on data models and semantic layers
  • Production experience with knowledge graphs and ontologies (e.g., Neo4j, Neptune)
  • Strong AWS proficiency including tools like CloudFormation, Glue, Lambda, and S3
  • Proficient in Python and SQL, with experience across various data stores
  • Experience supporting AI/ML systems and integrating data access with identity systems

Responsibilities

  • Lead design and evolution of knowledge graphs and ontologies for AI systems
  • Align disparate enterprise data into coherent, queryable graphs with clear provenance
  • Own and improve the retrieval substrate, including graph queries and vector indexes
  • Curate datasets and establish metrics for retrieval quality and grounding accuracy
  • Develop data models and build data pipelines in AWS using Python and SQL
  • Profile data sources and implement validation and monitoring processes
  • Collaborate on data governance and integrate with enterprise identity access policies

Benefits

  • Medical, dental, vision, and prescription drug coverage
  • Access to a Health Coach and Employee Assistance Program
  • Retirement savings plan with company matching and contributions
  • Tuition assistance and adoption assistance
  • Paid parental leave and disability insurance
  • Life insurance and paid time-off for vacation or illness
Full Job Description
Job Description Summary
The Senior Data Engineer designs and builds the AWS-native data foundation behind our enterprise AI applications — knowledge graphs, semantic layers, retrieval corpora, and the pipelines that keep them trustworthy. This role leads both the design strategy for how our AI systems understand enterprise data and the hands-on engineering to make it real. You will set the patterns the rest of the team — including citizen developers building with Agents and MCPs — follow when they access, curate, or extend our data.

Job Description

Roles and Responsibilities:

Knowledge Graph and Semantic Layer (primary focus)

  • Lead the design and evolution of the knowledge graphs and ontologies powering our AI's reasoning, retrieval, and explainability.
  • Align enterprise data (engineering handbooks, parts, service manuals, DMAIC records, user files) into a coherent, queryable graph with clear provenance across structured, semi-structured, and unstructured sources.
  • Own the retrieval substrate — graph queries, vector indexes, and hybrid retrieval — and drive measurable improvements in grounding quality.

AI/ML Data Quality

  • Curate grounding corpora, eval datasets, and retrieval benchmarks for LLM-based features.
  • Instrument metrics for retrieval quality, grounding accuracy, and freshness; drive regressions down over time.
  • Shape training and inference data contracts with AI engineers, including feedback loops from user signals.

Data Modeling and Pipelines on AWS

  • Produce conceptual, logical, and physical data models for operational and analytical workloads; establish modeling standards, naming conventions, and reuse patterns.
  • Build ingestion and transformation pipelines in Python and SQL using AWS services —Glue, Lambda, Step Functions, S3, Athena, OpenSearch, Neptune— and AI services such asBedrockandBedrock Knowledge Bases.
  • Author infrastructure as code inCloudFormation(CDK welcome) and apply AWS best practices for IAM, security, cost, and observability.
  • Profile sources, identify data quality gaps, and design automated validation, monitoring, metadata, and lineage.

Data Governance and Identity Integration

  • Partner with security and platform teams to integrate data access with enterprise identity and access policies, as we look to modernize for AI.
  • Define data contracts, attributes, and metadata that policy engines can reason over for attribute- and context-based access control.
  • Contribute to the technical data dictionary, business glossary, and data catalog.

Technical Leadership

  • Set the design direction for data and semantic modeling across the team.
  • Mentor engineers and citizen developers on modeling, ontology design, and retrieval engineering.
  • Communicate tradeoffs and value clearly to product, business, and executive stakeholders

Required Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a STEM field
  • A minimum of three years of data engineering experience

Eligibility Requirement:

  • Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.

Desired Qualifications:

  • 5+ years of hands-on data engineering with a track record ofdesigning 6 not just implementing 6 data models and semantic layers.
  • Production experience with knowledge graphs and ontologies (Neo4j, Neptune, TigerGraph, RDF/SPARQL, or similar) and graph query languages (Cypher, Gremlin, SPARQL).
  • Strong AWS proficiency required:CloudFormation (or CDK), Glue, Lambda, Step Functions, S3, IAM, Bedrock, Bedrock Knowledge Bases; OpenSearch and Neptune a plus.
  • Strong Python and SQL; comfort across relational, graph, vector, and document stores.
  • Experience supporting AI/ML or LLM systems 6 RAG pipelines, embeddings, eval datasets, grounding corpora.
  • Experience integrating data access with enterprise identity and policy systems
  • Strong cross-functional collaboration and communication, including technical presentations to non-data audiences.


Leadership Skills:

  • Ability to work effectively with multi-disciplinary teams (e.g., Digital Technology, GE Business teams) and understand the inter-dependencies between them.
  • Ability to showcase teamwork skills to achieve common goals, provide resolutions and share ideas.
  • Demonstrate the presentation and influencing skills


The base pay range for this position is $110,00-145,000. The specific pay offered may be influenced by a variety of factors, including the candidates experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan. This posting is expected to close on July 14th.

GE Aerospace offers comprehensive benefits and programs to support your health and, along with programs like HealthAhead, your physical, emotional, financial and social wellbeing. Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach from GE Aerospace; and the Employee Assistance Program, which provides 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions, as well as access to Fidelity resources and planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time-off for vacation or illness. 

This role will require in-person attendance for New Hire Orientation on Day 1

#LI-JR1

This role requires access to U.S. export-controlled information. Therefore, employment will be contingent upon the ability to prove that you meet the status of a U.S. Person as one of the following: U.S. lawful permanent resident, U.S. Citizen, have been granted asylee or refugee status (i.e., a protected individual under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3)).

Additional Information

Relocation Assistance Provided: No

#LI-Remote - This is a remote position

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