VP Engineering, Business AI Applications

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

Your Career

The VP Engineering, Business AI Applications, will be the principal technical leader responsible for integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities across CPQ and NPI ecosystems, with a core focus on the Opportunity-to-Quote lifecycle. This executive role demands a blend of visionary leadership, deep technical architecture expertise, and hands-on experience building and deploying enterprise-grade AI products. The successful candidate will not only set the technical direction for transforming business applications with an AI mindset, but will also be accountable for the execution and successful delivery of scalable, reliable, and high-impact AI solutions that drive significant business growth and efficiency.

About the Team

The Business Applications & Engineering organization is a critical driver of Palo Alto Networks’ operational and financial engine, engineering and scaling the enterprise business application portfolio that powers core corporate, customer, and revenue operations. As our business grows, we are executing a high-impact application transformation, embedding state-of-the-art AI microservices, autonomous agentic workflows, and Large Language Models (LLMs) directly into our business software systems to fundamentally redefine how enterprise teams operate across the company. This role sits at the intersection of business strategy and technical innovation, reporting directly to the SVP of Business Applications.

Your Impact

Technology Strategy & Roadmap: Define the multi-year technology strategy and architecture roadmap for AI integration into the Business App stack, focusing on maximizing business value in areas like intelligent automation, predictive forecasting, and generative AI-assisted selling.

AI Solution Architecture: Architect and establish company standards for advanced AI customer solutions, demonstrating viability through proof-of-concepts.

Go-To-Market Engineering: Lead Go-To-Market Engineering to scale pipeline generation and seller productivity through AI, automation, and data-driven execution.

Team Leadership: Lead and develop a global, multi-disciplinary team comprising AI solutions, full-stack, and SaaS developers, cultivating a collaborative, inclusive, and innovative culture.

Strategic Impact: Drive significant business impact by leading large-scale, multi-organizational, or global initiatives.

AI Governance and Ops: Drive an AI Ops culture to enable continuous evolution across all Business applications.

Performance and Optimization: Monitor, analyze, and optimize the performance, cost-efficiency, and operational health of all deployed AI models and solutions, driving continuous improvement through data-driven insights.

Qualifications

Your Experience

Leadership and Communication Exceptional people-management skills, acting as a Player/Coach to inspire and foster desired behaviors.

Outstanding verbal and written communication skills, coupled with executive presence.

Strong enterprise communication skills, business acumen, and financial understanding.

Proven track record of thought leadership (e.g., technical articles, conference speaking engagements, or open-source contributions).

Business and Strategic Acumen Extensive experience with Business applications, particularly the Opportunity to Quote lifecycle.

Excellent analytical skills and a demonstrated ability to translate detailed data analysis into actionable strategic insights to drive customer adoption and provide business recommendations.

Demonstrated ability to work effectively across internal and external organizations, building consensus and driving results.

Proven ability to reduce organizational friction and implement scalable mechanisms.

Technical Leadership Agentic AI & Generative Workflows Autonomous Sales & Commerce Agents: Proven experience building agentic workflows using frameworks like LangChain , LlamaIndex , AutoGPT , or CrewAI to automate multi-step commercial processes (e.g., automated RFPs, dynamic quote generation, automated lead nurture).

RAG (Retrieval-Augmented Generation): Deep expertise in architecting high-accuracy RAG pipelines using vector databases ( Pinecone , Milvus , Weaviate , Qdrant ) to ground LLMs in internal product catalogs, pricing rules, and sales collateral.

LLM Engineering & Fine-Tuning: Fine-tuning open-source models ( Llama 3 , Mistral ) vs. orchestrating proprietary foundation models ( OpenAI GPT-4 , Anthropic Claude , Google Gemini ); prompt engineering, guardrailing ( NeMo Guardrails ), and context window optimization.

Predictive Analytics & Machine Learning CPQ ML Engines: Hands-on architecture experience with personalized recommendation algorithms (Collaborative Filtering, Neural Collaborative Filtering, Graph Neural Networks), dynamic pricing engines, search relevance engines, and automated visual search.

NPI agents: Swarm os agents to help accelerate the NPI velocity looking at E2E Opty to cash lifecycle.

CPQ & Revenue Ecosystem Architecture Commercial Platform Integrations: Direct experience embedding AI microservices into enterprise CRM and Commerce suites, including Salesforce SAP Commerce Cloud / CX , Adobe Commerce / Magento , Commercetools , or Zuora .

Headless & Microservices Architecture: Experience deploying AI capabilities via API-first, composable architecture patterns (REST, GraphQL, gRPC) directly into customer-facing storefronts and seller interfaces.

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