Zscaler
5001 - 10000 employees
Founded 2008
🔒 Cybersecurity
☁️ SaaS
🏢 Enterprise
💰 Secondary Market on 2017-11
Cybersecurity • SaaS • Enterprise
Zscaler is a leading provider of cloud-based cybersecurity solutions, specializing in Zero Trust architecture. The company enhances security and connectivity for organizations by enabling seamless, secure access to applications and data across various environments, including the cloud, on-premises data centers, and IoT systems. With proven ROI and significant reductions in cybersecurity risks, Zscaler empowers enterprises to protect their digital resources while optimizing operational costs.
Principal GenAI Data Engineer
🕒 May 28
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Zscaler
5001 - 10000 employees
Founded 2008
🔒 Cybersecurity
☁️ SaaS
🏢 Enterprise
💰 Secondary Market on 2017-11
Cybersecurity • SaaS • Enterprise
Zscaler is a leading provider of cloud-based cybersecurity solutions, specializing in Zero Trust architecture. The company enhances security and connectivity for organizations by enabling seamless, secure access to applications and data across various environments, including the cloud, on-premises data centers, and IoT systems. With proven ROI and significant reductions in cybersecurity risks, Zscaler empowers enterprises to protect their digital resources while optimizing operational costs.
📋 Description
• 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
🎯 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)
🏖️ 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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