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Leading opportunity qualification, solution demonstrations, proposals, commercial discussions, and delivery economics for forward-deployed AI engineering work.

Zscaler

Principal GenAI Data Engineer

Bellevue, WA, United States
Santa Clara, CA, United States

$185,500 - $265,000 USD

Apply on job-boards.greenhouse.io About employer

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Job details

Pay: $185,500 - $265,000 USD
Work location: This is a Hybrid role based in Santa Clara, CA or Bellevue, WA (3 days in office), reporting to the Senior Manager, Enterprise AI Data Platform in the Information Technology Data Strategy department
Posting language: English
Posted: Nov 11, 2026

Original job description

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform.

We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler.

Role

We are looking for a Principal GenAI Data Engineer to join our team. This is a Hybrid role based in Santa Clara, CA or Bellevue, WA (3 days in office), reporting to the Senior Manager, Enterprise AI Data Platform in the Information Technology Data Strategy department.

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.

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 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

Who You Are

You’re comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback - knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking For

Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
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)

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 / GenAIOps frameworks such as LangSmith, Evaluation Framework like Arize Phoenix, Weights & Biases, or MLflow
Familiarity with Agent Frameworks like LangGraph, CrewAI, or Google ADK

Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.

The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.

Base Pay Range

$185,500 - $265,000 USD

At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

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

Learn more about Zscaler's hybrid working model and benefits here.

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.

Pay Transparency

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

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our 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.

Apply on job-boards.greenhouse.io About employer

More about this job

Skills

Unstructured data
Python
Collaboration
Data models
Teamwork
ML
Mlflow

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Work requirements

Jobs in the United States