Senior Principal AI Software Engineer, Palo Alto Networks

• This unique position allows us to innovate and implement the most advanced security solutions, setting the standard for the industry
• Bachelor’s degree or equivalent experience in Computer Science or a related field
• 12+ years of IT system architecture, design, and development experience, or 8+ years with a Master's degree, or 5+ years with a PhD
• Proven track record of technical leadership in Agile/Scrum environments, delivering large-scale implementations with aggressive timelines
• Expert-level proficiency in Python
• Extensive, hands-on experience building applications using Large Language Models (LLMs) such as Llama 3, GPT-4, and Anthropic
• Deep experience with Multi-Agent systems, Agent-to-Agent (A2A) communication, and orchestration frameworks

Desirable

• Information Technology - Our Information Technology team at Palo Alto Networks is at the forefront of securing our own digital landscape
• We're not just an IT department; we're the first customer of our groundbreaking cybersecurity products
• As a Sr Principal AI Engineer, you will join a dynamic team to pioneer our Generative AI transformation. You will act as a hands-on, technical leader, architecting the next generation of our business applications. This role moves beyond traditional software engineering to design intelligent, agentic workflows that will revolutionize our Go-To-Market (GTM) and customer experience processes
• You will join a dynamic and fast-paced team of seasoned fellow engineers designing and developing multi-tiered applications in a rapidly growing company. As a Sr Principal AI Engineer, you will leverage your extensive experience to act as the trailblazer, helping us build and innovate enterprise-grade full-stack systems with a specific focus on Generative AI transformation
• We are looking for a highly hands-on, extremely technical leader to architect the next generation of our internal and external business applications. You will move beyond traditional software engineering to design intelligent, agentic workflows that revolutionize our Go-To-Market (GTM) processes
• Architect a Proxy-First AI Ecosystem: Lead the design and implementation of an "AI Gateway" intermediary layer to ensure 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
• Deep System Visibility: Implement comprehensive observability pipelines specifically for GenAI to track trace-level data, prompt inputs/outputs, and model latency
• Cost & Performance Optimization: Create architecture that optimize performance and expense by routing simpler queries to cost-effective models
• Feedback Loops: Integrate observability data into the development cycle to identify bottlenecks, high-latency chains, and model drift in real-time
• Agentic AI Leadership: Institute and promote innovative thinking by incorporating agentic AI, designing sophisticated Multi-Agent Systems and Agent-to-Agent (A2A) workflows
• Business Workflow Automation: Apply GenAI to complex Go-To-Market (GTM) business logic, automating workflows such as customer support processes and entitlement platforms
• Evaluation Frameworks: Pioneer "LLM as a Judge" testing methodologies to automate quality assurance, using capable models to evaluate the correctness, tone, and helpfulness of system outputs
• AI Safety Implementation: Build robust guardrails to filter inputs and outputs, ensuring the prevention of PII exposure, offensive content, and prompt injection attacks
• Adversarial Defense: Develop detection mechanisms including keyword filtering, behavioral analysis, and adversarial training to protect model instructions from manipulation