Senior Product Manager (AI / Data Classification)

Zscaler accelerates digital transformation to ensure agility, efficiency, resilience, and security for its customers. They are seeking a Senior Product Manager (AI / Data Classification) to lead data classification capabilities within their Data Security platform, focusing on discovering and classifying sensitive data across various environments.

Responsibilities:

• Partner closely with a focused engineering, data science/ML, design, sales, and customer success to deliver accurate, scalable classification, clear policy outcomes, and measurable customer value
• Own the classification taxonomy, labeling standards, and policy model (custom categories, confidence thresholds, inheritance, overrides, exceptions)
• Drive accuracy improvements by managing precision/recall targets, sampling strategies, tuning workflows, and customer feedback loops
• Set requirements for scanning at enterprise scale (billions of objects, large tables), optimizing cost, latency, and coverage
• Define how the platform combines pattern-based detectors, NLP/ML, and LLM-assisted classification for structured and unstructured data

Requirements:

• Product Management experience, with meaningful ownership of data security/privacy products. Product management experience can be substituted with data science experience
• Demonstrated experience shipping products that use AI/ML and/or LLMs in production, with a strong understanding of data classification approaches across structured and unstructured data
• Expertise in evaluation and quality measurement for classification systems and building/maintaining golden datasets
• Ability to design human-in-the-loop workflows for high-stakes labels, covering review/approval, exception handling, and audit trails
• Experience driving cost/performance tradeoffs for AI at scale, including token/compute budgeting, model selection, and managing latency for large corporations
• Strong technical collaboration skills with ML engineering and data science
• Familiarity with embedding-based similarity and semantic retrieval for classification and deduping (vector DBs, ANN indexing, chunking strategies)
• Prior work in DSPM/DLP/CASB/insider risk where false negatives have high blast radius and you have designed processes to manage that risk