Principal IT Software Engineer, Go-To-Market (GTM) and CX Products

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

Job Summary

As a Principal IT Software Engineer to join our CPQ (Configure Price and Quote) team, you will serve as the recognized subject matter expert, bringing industry best practices to our architectural design. You will act as a technical leader, using first-principles thinking to dissect complex challenges and drive the development of company objectives. This role requires working autonomously to lead cross-functional teams in creating an AI-Led, Secure, Scalable CPQ Platform that transforms our business processes.

Key Responsibilities

• Architect and design scalable, highly reliable business systems across multiple services and teams, ensuring alignment with long-term technical strategy.
• Lead the technical design and architecture of an AI-Led, Secure, Scalable CPQ Platform, owning the process from prototype through deployment.
• Build and integrate foundational and agentic AI/ML workflows, ensuring the secure and effective use of GenAI technologies in our products.
• Establish and enforce engineering standards and best practices within an agile development environment to improve code quality and team velocity.
• Proactively collaborate with product and business teams to balance technical debt, product stability, and new features against go-to-market timelines.
• Mentor and empower Staff engineers, challenging team members at all levels to grow their technical and problem-solving skills.
• Establish evaluation and observability frameworks to measure AI quality (e.g., accuracy, hallucination rates) and overall system reliability.
• Apply deep understanding of prompt engineering best practices and LLM security considerations, such as input validation and prompt injection prevention.

• Bachelor's degree with a minimum of 12 years of related experience; or a Master's degree with 8 years of experience; or a PhD with 5 years of experience.
• Proven experience designing and developing scalable web applications and integrations using a microservices architecture.
• Expert-level server-side software development experience using Java with Spring/Spring Boot; experience with Go is a plus.
• In-depth knowledge of object-oriented programming, data structures, algorithms, and software design patterns.
• Demonstrated experience building production-grade applications with LLM APIs such as Google Vertex AI/Gemini, OpenAI, or Anthropic.
• Hands-on experience with CI/CD platforms and tools including Kubernetes, Jenkins, Git, Spinnaker, or Docker.
• Must be located in the SF Bay Area and able to work in a hybrid/onsite capacity.

• Experience architecting conversational AI platforms, chatbots, or Text-to-SQL systems.
• Knowledge of multi-turn dialogue management and conversation history patterns in AI applications.
• Professional development experience with TypeScript/Node.js for AI agent development.
• Familiarity with vector embeddings, semantic search, and similarity-based retrieval patterns for RAG systems.