Senior Principal Program Manager, Enterprise AI

Our Mission

At Palo Alto Networks®, we're united by a shared mission-to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you're ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you're in the right place.

Who We Are

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That's why most of our teams work from the office full time, with flexibility when it's needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

Job Summary

The Mission

We are seeking an execution-focused Principal Program Manager to drive the industrialization of our Enterprise AI initiatives. In this role, you will move beyond traditional project management to become an outcome orchestrator for our "AI Idea-to-ROI" lifecycle.

Unlike traditional deterministic software, AI development is experimental and probabilistic. You will lead cross-functional AI Pods through complex discovery, validation, and deployment loops, ensuring that we "Fail Fast" on bad ideas and aggressively scale high-value solutions. You will be the guardian of the playbook, ensuring that every AI initiative-from "Copilots" to "Agents"-has a mathematically proven path to business value before it enters production.

Your Impact

• Drive the AI Development and Rollout Lifecycle: Operationalize our proprietary AI development lifecycle, guiding teams through rigorous gate-checks for Problem Fit, Data Fit, and Process Fit to ensure high success rates.
• Orchestrate "AI Pods": Act as the "connective tissue" between Product Managers, AI Engineers, Data Engineers, and Business Subject Matter Experts, ensuring these diverse personas collaborate effectively within the AI lifecycle.
• Enforce Quality over "Vibes": Shift the culture from subjective testing to scientific evaluation, ensuring deliverables like "Golden Sets" and "Evaluation Harnesses" are prerequisites for launch.
• Accelerate "Kill Switch" Decisions: Empower leadership to make hard pivot/kill decisions early by surfacing clear data on feasibility risks and data readiness.

• Lead the timely execution of AI initiatives, managing the non-linear loops of Code, Data, and Model development.
• Apply the Feasibility Framework (assessing Stakes, Checkability, Accuracy, Latency, Economics) during the intake phase to identify "Traps" vs. "Sweet Spots" for Generative AI.
• Apply the Data Readiness Framework (assessing Security, Hygiene, Attributes, Rationale, Proven Examples) to determine if datasets are ready for enterprise AI ingestion.
• Facilitate "Kill Switch" reviews at key stage gates to prevent "zombie pilots" that never deliver Return on Investment.

• Coordinate the workflow of the AI Pod, ensuring clear handoffs between the Strategy Layer (Product Mgr), Model Layer (AI Eng), and Data Layer (Data Eng).
• Ensure the timely creation of modern AI deliverables, including Product Requirements Docs with defined "Error Budgets," Golden Sets (Acceptance Criteria), and System Architecture Docs.
• Manage dependencies for Infrastructure-as-Code and Guardrails Configuration to ensure the "Compound AI System" is deployed securely and reliably.

• Drive Process Fit using the Process Design Framework, ensuring AI agents reduce steps and are embedded in the flow of work rather than creating new "chat portals" that users ignore.
• Partner with Business Subject Matter Experts to define Process Swimlanes and Operations Runbooks for "Human-in-the-Loop" handling of AI hallucinations.
• Establish Model Observability metrics (Cost, Latency, Feedback Loops) to prevent silent model decay in production.

• Bachelor's degree in a technical field or equivalent practical experience.
• 12+ years of technical program management experience with a proven track record of delivering complex, cross-functional technology initiatives on a global scale.
• Deep understanding of the differences between Traditional Software (Deterministic) and AI Software (Probabilistic) development lifecycles.
• Expert-level ability to distill complex technical concepts into clear, concise business narratives and strategy documents for executive decision-making.

• Master's or PhD in a relevant technical field.
• Prior experience in Management Consulting (Big 4 or Strategy firm) with a proven toolkit for structuring ambiguity and managing senior stakeholder expectations.
• Hands-on experience managing projects involving Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or Agentic workflows.
• Experience with 'Golden Sets,' 'Evaluation Harnesses,' or similar ground-truth testing methodologies to enforce data-driven launch criteria.