Principal GenAI Data Engineer
About The Position
We are looking for a Principal GenAI Data Engineer to join our IT Data Strategy team. This role is fully remote within the US, reporting to the Senior Manager, Enterprise AI Data Platform. We are seeking an experienced technical leader to drive the design and implementation of enterprise-grade Generative AI data ingestion, knowledge preparation, and platform architectures that enable scalable, production-ready GenAI applications. This role focuses on architecting robust pipelines and platforms for ingesting, processing, governing, and serving structured and unstructured enterprise data for AI/LLM workloads. The ideal candidate combines deep expertise in enterprise data architecture, unstructured data pipelines, GenAI platform engineering, and strong software engineering skills in Python.
Requirements
- Expert-level Python programming and software engineering capabilities
- Experience building distributed/scalable data pipelines for AI workloads
- Strong understanding of unstructured data extraction and processing pipelines
- Experience with vector databases, graph databases, and metadata/knowledge storage systems
- Hands-on experience with clustering, entity recognition algorithms, and modern retrieval strategies (including RAG, search, and agentic AI workflows)
Nice To Haves
- Deep understanding of AI-ready data platform design principles and the ability to bridge platform/data engineering with GenAI/LLM application requirements
- Experience with LLMOps / GenAIOps frameworks such as LangSmith, Evaluation Framework like Arize Phoenix, Weights & Biases, or MLflow
- Familiarity with Agent Frameworks like LangGraph, CrewAI, or Google ADK
Responsibilities
- Architect enterprise-scale GenAI data platforms for ingestion, transformation, enrichment, and serving of structured and unstructured data
- Design scalable pipelines for enterprise knowledge ingestion from diverse data sources including documents, SaaS platforms, knowledge bases, collaboration tools, and databases
- Define architecture for metadata extraction, chunking, enrichment, embeddings generation, and knowledge preparation workflows
- Design AI-ready data models and storage strategies for vector, graph, and hybrid knowledge systems
- Architect scalable unstructured data processing pipelines for text, images, PDFs, tables, and multimodal content
Benefits
- Various health plans
- Time off plans for vacation and sick time
- Parental leave options
- Retirement options
- Education reimbursement
- In-office perks, and more!
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
