AI-First Core IT Software Engineering: Software, ML & Data (Staff – Principal)

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 We are hiring AI Engineers at multiple levels (Lead/Staff through Senior Principal) to join our IT Business Applications team. This group builds and operates the technology platforms that power Marketing, Sales, and the full Lead-to-Cash lifecycle. This is a solutions engineering role, not a data science or ML research role. You will act as a hands-on technical leader who uses AI as building blocks—LLMs, agents, RAG, embeddings—to deliver production solutions that solve real business problems. You will partner directly with business and product stakeholders, translate requirements into scalable architecture, and own delivery end-to-end from design through production operations. You will move beyond traditional software engineering to design intelligent, agentic workflows that revolutionize our Go-To-Market (GTM) and customer experience processes—ensuring our platforms are the most secure and efficient in the industry, directly improving operational revenue generation. Your Impact AI Architecture & Solution Design Business-to-Architecture Translation: Partner with business and product teams to deeply understand requirements. Translate business intent into scalable, modern technical architectures that meet non-functional requirements (performance, reliability, scalability, security, observability). AI Gateway Architecture: Architect a Proxy-First AI Ecosystem—an intermediary layer that ensures vendor independence, allowing seamless switching between LLMs (e.g., GPT-4, Llama, Anthropic) without refactoring core application code. Unified API Design: Build a single, unified API endpoint that abstracts the complexities of individual LLM providers, providing centralized control for access and security. Technology Selection: Evaluate and choose the right architecture patterns for each use case—selecting from agentic, RAG, workflow-based, hybrid, or traditional engineering approaches based on problem characteristics. Build vs. Buy Decisions: Make principled technology choices. Design for maintainability, extensibility, and operational excellence. GenAI & Multi-Agent Systems Agentic AI Development: Design and build sophisticated Multi-Agent Systems and Agent-to-Agent (A2A) workflows capable of planning, multi-step execution, self-correction, and collaboration with humans or other agents. Business Workflow Automation: Apply GenAI to complex GTM business logic—automating workflows such as customer support, sales compensation, entitlement platforms, and partner channel operations. Lead-to-Cash Transformation: Own end-to-end delivery of MarTech and FinTech initiatives, from technical design to operational readiness, leveraging AI to transform quote-to-cash processes. Advanced Reasoning Pipelines: Develop retrieval systems, knowledge graph integrations, and reasoning pipelines that support autonomous task execution. AI Observability & Quality LLM Observability: Implement comprehensive observability pipelines for GenAI—tracking trace-level data, prompt inputs/outputs, model latency, and cost. Cost & Performance Optimization: Design architecture that routes queries to the optimal model based on complexity, balancing performance and expense. Evaluation Frameworks: Pioneer "LLM as a Judge" testing methodologies—using capable models to evaluate the correctness, tone, and helpfulness of system outputs. Establish golden datasets for ground truth testing. Feedback Loops: Integrate observability data into the development cycle to identify bottlenecks, high-latency chains, and model drift in real-time. Security & Governance AI Safety Implementation: Build robust guardrails to filter inputs and outputs—preventing PII exposure, offensive content, and prompt injection attacks. This is a cybersecurity company; security-first thinking is non-negotiable. Adversarial Defense: Develop detection mechanisms including keyword filtering, behavioral analysis, and adversarial training to protect model instructions from manipulation. Graceful Degradation: Design systems that are resilient to AI component failures with proper fallbacks. Leadership & Communication End-to-End Ownership: Drive solution development from prototype to production, ensuring scalability, reliability, and performance. Stakeholder Communication: Communicate complex technical decisions and trade-offs clearly to both engineering peers AND business stakeholders/executives. Mentorship: Mentor and guide engineers, elevating engineering practices across the organization. Cross-Team Influence: Lead high-ambiguity, cross-team technical initiatives and drive alignment. Qualifications Qualifications Required   Lead / Staff - 8+ years Principal - 12+ years (or 8+ with Ma