Principal IT Product Manager, Post Sales

Palo Alto Networks•Office - USA - CA - Headquarters, CA

1d•$164,000 - $266,000•Onsite

About The Position

Palo Alto Networks is seeking a Principal IT Product Manager with an End-to-End (E2E) process mindset to lead the strategic vision and transformation of our post-sales customer ecosystem. In this role, you will look at the customer journey through a holistic lens: from the moment a customer purchases a product, through deployment, consumption, to ongoing technical support and telemetry that drives an overall account health management. Leveraging first-principles thinking, you will break down complex, siloed operational tracks and architect AI-enabled, agentic solutions that simplify processes, eliminate friction, and accelerate value delivery. You will design systems where AI agents operate autonomously or with a human-in-the-loop, utilizing generative conversational AI to revolutionize how our customers deploy, utilize, and support their investments. This role requires a unique blend of deep data-driven empathy for the customer journey and cutting-edge technical product management expertise to directly influence both our Product and Global Customer Service (GCS) organizations. Translate business objectives into a clear and actionable Application Product Roadmap and execute a holistic product strategy spanning Salesforce, Gainsight, Clarizen, Custom-built applications, and the broader post sales ecosystem.

Requirements

12+ years of product management experience in enterprise technology, IT Post-Sales, or Customer Experience (CX) domains, with a proven track record of launching scalable, AI-powered solutions.
E2E Process Thinker: Demonstrated experience tracking a customer’s post-sales journey across distinct domains such as entitlement management, consumption, activation and provisioning, customer success and support.
First-Principles Mindset: Ability to peel back layers of legacy workflows to understand raw data flows, using logic to reconstruct elegant, simplified architectures from scratch.
Deep expertise in Agentic AI systems, including hands-on experience structuring workflows for autonomous agents, human-in-the-loop validation, and generative conversational frameworks.
Proven experience integrating AI solutions with core enterprise platforms like Salesforce Gainsight, Clarizen or other custom applications.
Exceptional communication skills, with the ability to articulate complex AI agent logic and E2E journey visions to both technical engineering teams and non-technical executive leadership.
Proficiency in Agile/Scrum methodologies, with a track record of leading sprint planning and backlog grooming specifically within an AI or advanced data development context.

Nice To Haves

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with a strong emphasis on AI/ML preferred.

Responsibilities

E2E Customer Journey Mapping & Vision: Analyze the comprehensive post-sales customer lifecycle, linking the initial purchase to licensing/entitlement activation, deployment hurdles, feature consumption, and support ticket creation.
Bridge operational silos by mapping how a technical support case or telemetry alert triggers upstream adjustments in deployment workflows or consumption tracking contributing to customer overall health.
Act as the primary architect of a unified, actionable Application Product Roadmap across Salesforce, Gainsight, custom applications, and telemetry data lakes.
Agentic Process Design: Identify manual friction points in the service and lifecycle chains, replacing them with "Agent-Native" architectures to automate complex tasks.
Design and deploy autonomous or human-in-the-loop AI agents capable of reasoning through complex deployment blocks, license usage imbalances, or feature adoption gaps.
Infuse generative conversational AI into customer-facing and internal touchpoints to deliver predictive, proactive, and deeply personalized experiences.
Telemetry & Predictive Support Orchestration: Leverage advanced analytics, machine learning platforms, and real-time product telemetry data to identify patterns in case trends and engineering escalations.
Design features that correlate support requests with specific deployment phases versus active consumption anomalies, proactively prioritizing platform fixes and preventing future customer issues.
Ensure data feeds from infrastructure and cloud systems are structurally optimized to empower AI models to anticipate user needs before an issue is manually reported.
AI-Augmented Prototyping & Delivery: Maintain a "Builder" mindset, moving beyond static PRDs by using AI-assisted tools (e.g., LLMs, low-code builders) to construct "Living Specs"—functional prototypes that validate data flows and API logic prior to engineering handoff.
Own the complete product lifecycle from ideation to delivery, writing precise epics and user stories with an AI-first lens embedded as part of the AI SDLC.
Serve as the central cross-functional bridge among Business units, R&D, IT Architecture, Data Engineering, and QA to bring intelligent ecosystem solutions to fruition.
Metrics & Governance: Establish and monitor comprehensive success criteria and KPIs for AI-powered features, tracking model performance, data quality, agent execution accuracy, and tangible ROI.
Champion AI product management best practices within the organization, mentoring junior team members and evangelizing the power of AI to solve complex business problems.