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# Distinguished Engineer - AI-First Transformation

- **Company:** Palo Alto Networks
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cyber Security, Large Language Models, Data Strategy
- **Published:** July 8, 2026
- **Apply:** https://dejobs.org/x/x/587C979CA9C542AEADB5E9CC86859AC0/job/

## About the Role

* Bachelor's degree with 15 years of related experience, or Master's degree with 12 years of experience, or PhD with 8 years of experience.
 * Deep experience leading cross-functional teams at the intersection of Business Strategy and Technical Execution.
 * Proven 'General Manager' mindset with a track record of owning the P&L or business outcome of a digital product.
 * Fluency in the modern AI stack, understanding the capabilities and limitations of LLMs, RAG architectures, and Agentic workflows., * Ability to translate complex concepts between CXOs (Business Outcomes), CIOs (Architecture/Security), and Data Scientists (Models/Weights).
 * Technical fluency to design workflows that handle ambiguity and require human-in-the-loop validation.
 * Demonstrated success in change management, driving technology adoption, managing automation concerns, and upskilling teams.

## Description

We are seeking a visionary Distinguished Engineer to drive our AI-First Transformation, bridging the gap between AI technology and business impact. You will re-imagine how our enterprise operates by rewriting operational workflows to drive efficiency, personalization, and speed. Your goal is to build a scalable 'AI Factory' that moves the organization from ad-hoc pilots to industrialized business value by leading the end-to-end AI lifecycle and translating ideas into tangible business outcomes., * Define the AI transformation roadmap, ruthlessly prioritizing initiatives like autonomous agents and predictive operations to ensure a clear path to ROI.

 * Oversee the data strategy, curating 'Golden Examples' from institutional history to train models on our best work and digitize our 'Enterprise Memory'.
 * Re-imagine and design 'Invisible AI' workflows that seamlessly assist human experts, rather than simply digitizing existing processes.
 * Establish rigorous 'Report Cards' for AI models to move from 'vibes-based' decisions to structured evaluation, measuring accuracy, latency, and business relevance before production.
 * Partner with Legal, InfoSec, and Engineering to implement strict governance and safety 'Circuit Breakers,' protecting company IP and preventing data leaks or unsafe AI actions.
 * Own the adoption curve and unit economics, ensuring workforce trust in AI tools and preventing model decay by maintaining a fresh knowledge base.


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