Principal AI Research Engineer

Zscaler

Principal AI Research Engineer at Zscaler defining AI integration strategies and leading secure AI initiatives. Building developer ecosystems and driving partnerships for growth in AI security.

Posted 7/30/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $171,500 - $245,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining AI Ecosystem Strategy and leading the Secure AI roadmap, with a strong focus on building developer ecosystems through APIs and SDKs. Possesses deep technical fluency in AI lifecycle management and a foundational understanding of AI/ML technologies to drive impactful solutions.

Highest-signal resume keywords

AI Ecosystem StrategySecure AI RoadmapTechnical LeadershipAI Lifecycle ManagementAPIs and SDKs Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI LifecycleTraining vs. InferenceGPU RolesContext WindowsRAG ArchitecturesFirst-Principles ThinkingEnterprise LLM DeploymentMVP DevelopmentAI/ML TechnologiesData Leakage Prevention

Soft Skills

Bias for ActionIterative Development

Industry Keywords

Technical PartnershipsCross-Functional CollaborationZero Trust-native ApplicationsHigh-Growth Go-to-MarketDeveloper Ecosystem

About the role

Key responsibilities & impact

Define the AI Ecosystem Strategy by leading the vision for integrations with frontier model providers, vector database companies, and AI infrastructure leaders
Lead the "Secure AI" roadmap by owning the lifecycle for features that enable safe use of 3rd-party LLMs and prevent data leakage
Build a developer ecosystem by defining and launching APIs, SDKs, and integration patterns for "Zero Trust-native" applications
Drive market leadership and cross-functional partnerships to turn complex technical integrations into high-growth go-to-market motions

Requirements

What you’ll need

8+ years of experience in technical leadership or engineering partnerships with a history of building impactful industry relationships
Deep technical fluency in the AI lifecycle including training vs. inference, GPU roles, context windows, and RAG architectures
Ability to apply first-principles thinking to fundamental security and networking challenges in enterprise LLM deployment
Strong bias for action with a "Ship Early, Iterate Fast" mentality and focus on delivering high-value MVPs
Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain

Benefits

Comp & perks

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