Protegrity

Protegrity

California · $197,900 – $221,200 · Remote

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Protegrity

San Francisco, CA · $185,900 – $204,100 · Remote

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Protegrity

Menlo Park, CA · $209,100 – $234,100 · Remote

This role involves building backend systems that integrate generative AI safely into enterprise products, using Python, Kubernetes, and vector databases. It suits experienced backend engineers who want to work at the intersection of AI systems and data security infrastructure.

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Protegrity

Fairfield, CT · $199,200 – $217,500 · Remote

Lead 2-3 engineering teams building scalable, modular front-end systems with React and micro-frontend architecture. This role suits experienced engineers who combine deep technical expertise with people leadership and want to stay hands-on while setting platform direction for multiple product teams.

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Protegrity

Fairfield, CT · $197,600 – $229,500 · Remote

A senior customer success leader who guides large enterprises through modernizing their data security infrastructure and adopting AI-powered data protection solutions. This role suits technically deep professionals who thrive in complex technical sales environments and want to shape how Fortune 500 companies protect data in the AI era.

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Protegrity

Fairfield, CT · $183,000 – $200,400 · Remote

Lead program management strategy and execution across Protegrity's product portfolio, coordinating cross-functional teams to deliver enterprise data security initiatives on time and on budget. This role suits experienced delivery leaders who can scale governance frameworks, manage complex dependencies, and build high-performing program management organizations in fast-moving tech environments.

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Protegrity

Connecticut, New York · $237,600 – $266,700 · Remote

Design and build the ontology and reasoning layer for Protegrity's data security platform, formalizing complex domains into entities and rules that support deterministic machine reasoning with full traceability. This role suits engineers with strong foundations in logic, graph systems, and formal modeling who want to bridge LLM-powered data extraction with auditable, explainable reasoning.

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