VP Business Applications Applied AI (GTM & NPI)

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!

Job Summary

Your Career

We are seeking a visionary, technically elite VP Business Applications Applied AI (GTM & NPI) to lead the AI-driven transformation of the platforms powering Palo Alto Networks’ multi-billion-dollar revenue engine. This executive leadership role owns the end-to-end product vision, technical architecture, and delivery of intelligent, agentic systems that redefine Sales, Partner, and New Product Introduction (NPI) capabilities through AI-first engineering.

Your Impact

Strategic Vision & AI-Native Technical Roadmap

Architect and own the long-term technical vision and multi-year roadmap for embedding advanced AI across the entire Go-To-Market (GTM) stack. Translate corporate strategy into a rigorously prioritized portfolio of AI initiatives, each grounded in measurable business impact, robust engineering delivery frameworks, and production-grade AI/ML standards.

• AI-Led Reimagination of Sales & Partner Experiences
  • Apply first-principles thinking to redesign the Order-to-Cash (O2C) / Quote-to-Cash (Q2C) workflow as a fully AI-native, agentic system.
    • Design and champion agentic AI experiences for sellers and partners — moving beyond traditional SaaS UIs to autonomous, multi-agent orchestration that handles conversational quoting, intelligent deal orchestration, automated prospecting, and real-time decision support.
    • Lead ground-level architectural discussions on AI-native seller workflows, including LLM-driven reasoning, tool-calling agents, memory systems, and human-in-the-loop guardrails.
    • Champion an AI-first engineering mindset: simplify legacy processes and re-engineer them with Generative AI, retrieval-augmented generation (RAG), and multi-agent systems to eliminate friction and dramatically accelerate lead-to-cash velocity.
• Solution Design & AI Architecture Leadership
  • Bring a hands-on solution architect and systems designer mindset (architect first, not just implementer).
    • Define scalable AI system architectures for GTM workflows that leverage LLMs, agentic frameworks, vector databases, orchestration layers, and real-time inference.
    • Prototype, validate, and iterate on high-impact AI concepts through rapid proof-of-concept engineering.
    • Own the full AI SDLC across GTM platforms.
    • Drive user-centric AI innovation in seller and partner portals, ruthlessly removing friction through intelligent automation, predictive insights, and hyper-personalized experiences.
• NPI & Q2C AI Engineering
  • Lead the technical strategy and AI architecture for New Product Introduction (NPI), building repeatable, intelligent machinery that enables seamless CPQ readiness, billing configuration, revenue recognition, and pricing intelligence from Day 1.
    • Partner with Product, Finance, and Engineering executives to design agentic NPI workflows that balance speed-to-market with revenue integrity.
    • Redesign core Q2C processes from first principles using AI-native data flows, automated configuration engines, and intelligent validation agents.
• Platform Ownership & Delivery Excellence
  • Translate complex business strategies into precise technical requirements, scalable AI architectures, and production delivery plans.
  • Establish rigorous cross-functional governance for AI initiatives, including backlog prioritization, risk management, model governance, and responsible AI practices.
  • Maintain platform health by balancing innovation velocity with foundational stability, scalability, and technical debt reduction across Salesforce, ERP integrations, CPQ engines, and custom AI layers.
  • Lead, mentor, and scale a high-performing global team of AI engineers, solution architects, ML specialists, data engineers, and business system analysts. Operate with a player-coach mindset — deeply engaged in architecture and technical direction while building organizational AI engineering excellence.

Qualifications

Your Experience

• 20+ years of progressive leadership in enterprise technology with at least 5+ years in a VP or equivalent executive role at a high-growth, large-scale tech or SaaS company.

• Deep AI Engineering expertise: Demonstrated success leading the design, development, and operation of production-grade AI/ML systems, including generative AI applications, agentic architectures, and large-scale automation.

• Strong GTM domain knowledge combined with hands-on experience in CRM (Salesforce), PRM, advanced CPQ, billing systems, and complex revenue architectures.

• Proven track record transforming seller/partner experiences through agentic AI, intelligent automation, and data-driven platforms.

• Experience leading large-scale digital and AI transformation programs with measurable impact on revenue operations.

• Technical credibility to influence and partner with C-suite executives, Product Engineering, and AI research teams.

• Hands-on familiarity with modern AI tech stack (LLMs, agent frameworks, GCP or equivalent cloud, MLOps, vector search, real-time systems) alongside core GTM platforms (Salesforce, Clari, Varicent, etc.).

• Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree (MS/PhD) or MBA strongly preferred.

Preferred Qualifications

• The Dual-Mindset: Proven ability to drive disruptive AI innovation while maintaining the reliability, compliance, and stability required for mission-critical revenue systems.

• Strong product engineering rigor - data-driven decision making, experimentation frameworks, system health monitoring, and business value quantification.

• Deep experience with hybrid hardware/software/SaaS go-to-market models and the technical complexities of NPI in such environments.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

Our Commitment

We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together.

We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at  [email protected].

Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.

All your information will be kept confidential according to EEO guidelines.