Principal GenAI Data Engineer

Zscaler, Inc.; San Jose (CA); Híbrido; USD 186.000 - 265.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health plans

Paid time off

Parental leave

Retirement plan

Education reimbursement

In-office perks

Descripción de la vacante

Zscaler is building enterprise capabilities for scalable, production-ready Generative AI, and the Principal GenAI Data Engineer role plays a central part in that effort. In this hybrid position based in San Jose, CA, you will design data ingestion, knowledge preparation, and platform architectures that power AI/LLM workloads across structured and unstructured content.

You will report to the Senior Manager, Enterprise AI Data Platform within IT Data Strategy and collaborate with cross-functional

Formación

• Expert-level Python programming and software engineering
• Experience building distributed data pipelines for AI workloads
• Unstructured data extraction and processing pipelines
• Familiar with vector and graph databases
• Knowledge of retrieval strategies like RAG and agentic AI workflows

Responsabilidades

• 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 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

Conocimientos

Python

Distributed data pipelines

Unstructured data processing

Vector databases

Graph databases

Metadata storage

Entity recognition

RAG

Herramientas

LangSmith

Arize Phoenix

Weights & Biases

MLflow

LangGraph

CrewAI

Google ADK

Descripción del empleo

Zscaler is building enterprise capabilities for scalable, production-ready Generative AI, and the Principal GenAI Data Engineer role plays a central part in that effort. In this hybrid position, you will help design the data ingestion, knowledge preparation, and platform architectures that power AI/LLM workloads across structured and unstructured enterprise content. You will report to the Senior Manager, Enterprise AI Data Platform within the Information Technology Data Strategy organization.

Based in San Jose, CA (hybrid), this role focuses on engineering robust pipelines and data systems that enable GenAI applications, including metadata extraction, embeddings generation, and retrieval-oriented serving patterns.

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 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

Requirements

• Foundational understanding of AI/ML technologies, with experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes in your functional domain
• Expert-level Python programming and software engineering capabilities
• Experience building distributed and scalable data pipelines for AI workloads
• Strong understanding of unstructured data extraction and processing pipelines
• Experience with vector databases, graph databases, and metadata or knowledge storage systems
• Hands-on experience with clustering, entity recognition algorithms, and modern retrieval strategies including RAG, search, and agentic AI workflows

Technologies

• Python
• RAG
• Vector databases
• Graph databases
• LangSmith
• Arize Phoenix
• Weights & Biases
• MLflow
• LangGraph
• CrewAI
• Google ADK

Role Details

• Hybrid role based in Santa Clara, CA or Bellevue, WA with 3 days in office
• Reports to the Senior Manager, Enterprise AI Data Platform in the Information Technology Data Strategy department

What You'll Do

• Architect enterprise-scale GenAI data platforms for ingestion, transformation, enrichment, and serving of structured and unstructured data
• Design scalable pipelines for enterprise knowledge ingestion across documents, SaaS platforms, knowledge bases, collaboration tools, and databases
• Define workflows for metadata extraction, chunking, enrichment, embeddings generation, and knowledge preparation
• Design AI-ready data models and storage strategies for vector, graph, and hybrid knowledge systems
• Architect unstructured data processing pipelines for text, images, PDFs, tables, and multimodal content

What Will Make You Stand Out

• Advanced experience architecting real-time distributed vector search infrastructure and multi-modal knowledge graph pipelines for enterprise-grade Retrieval-Augmented Generation (RAG) applications
• Experience with LLMOps and GenAIOps frameworks such as LangSmith, Arize Phoenix, Weights & Biases, or MLflow
• Familiarity with agent frameworks such as LangGraph, CrewAI, or Google ADK

Benefits

• Various health plans
• Time off plans for vacation and sick time
• Parental leave options
• Retirement options
• Education reimbursement
• In-office perks, and more!

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules.

Accommodation

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

Compensation: USD 185,500 - 265,000 per yearly.