Sr Director IT Engineering, GTM AI Applications
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What you'll do
- Define the multi-year technology strategy and architecture roadmap for AI integration into the GTM stack, focusing on maximizing business value in areas like intelligent automation, predictive forecasting, and generative AI-assisted selling.
- Architect and establish company standards for advanced AI customer solutions, demonstrating viability through proof-of-concepts.
- Lead Go-To-Market Engineering to scale pipeline generation and seller productivity through AI, automation, and data-driven execution.
- Lead and develop a global, multi-disciplinary team comprising AI Solutions, full-stack, and SaaS developers, cultivating a collaborative, inclusive, and innovative culture.
- Drive significant business impact by leading large-scale, multi-organizational, or global initiatives.
- Drive AI ops culture to drive continuous evolution of all GTM applications.
- 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.
What they're looking for
- 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, business acumen, and financial understanding.
- Proven track record of thought leadership (e.g., technical articles, conference speaking, open source contributions).
- Extensive experience with Go-to-Market (GTM) 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.
- Proven experience building agentic workflows using frameworks like LangChain, LlamaIndex, AutoGPT, or CrewAI to automate multi-step commercial processes.
- 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.
- 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.
- 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.
Nice to have
- Master's Degree or PhD in Engineering or a related STEM field is preferred.
- 15+ years of experience in Product Application Engineering.
- Expertise in enterprise AI productivity tools and platforms.
- Proven experience in leveraging AI and automation to modernize governance. Demonstrated success in transitioning programs from manual, spreadsheet-based processes to automated, self-healing platforms.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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 Sr. Director IT Engineering , GTM AI Applications, will be the principal technical leader responsible for integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities across our Go-to-Market (GTM) technology ecosystem, 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 in building and deploying enterprise-grade AI products. The successful candidate will not only set the technical direction for transforming GTM 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 GTM Technology team is a critical enabler of the company's revenue engine, responsible for the platform and applications that support Sales,and CPQ. We are embarking on a major transformation, leveraging cutting-edge AI technologies, particularly Large Language Models (LLMs), to fundamentally redefine how our GTM teams operate, from lead generation and opportunity management to proposal generation and quoting. This role sits at the intersection of business strategy and technical innovation, reporting directly to the SVP of GTM Technology.
Your Impact
Technology Strategy & Roadmap: Define the multi-year technology strategy and architecture roadmap for AI integration into the GTM 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.
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 AI ops culture to drive continuous evolution of all GTM 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, business acumen, and financial understanding.
Proven track record of thought leadership (e.g., technical articles, conference speaking, open source contributions).
Business and Strategic Acumen
Extensive experience with Go-to-Market (GTM) 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
1. 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.
2. 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.
Sales Intelligence ML: Predictive lead scoring, opportunity win/loss modeling, churn prediction, account propensity-to-buy (P2B) scoring, and automated deal health assessments.
3. 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.
4. MLOps, LLMOps & Enterprise Infrastructure
Production MLOps: Enterprise experience with ML lifecycle management platforms (MLflow, Kubeflow, Databricks, AWS SageMaker, Vertex AI), model drift detection, automated retraining loops, and A/B testing infrastructure.
Preferred Qualifications
Master's Degree or PhD in Engineering or a related STEM field is preferred.
15+ years of experience in Product Application Engineering.
Expertise in enterprise AI productivity tools and platforms.
Modernization Mindset: Proven experience in leveraging AI and automation to modernize governance. Demonstrated success in transitioning programs from manual, spreadsheet-based processes to automated, self-healing platforms.
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.
$264,300.00 - $362,725.00/yrOur 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 accommodations@paloaltonetworks.com.
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.
Is role eligible for Immigration Sponsorship?: Yes
Company
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