Principal/Sr. Principal AI Engineer - IT Business Applications

Palo Alto Networks•Office - USA - CA - Headquarters, CA

2d•$185,200 - $299,475•Onsite

About The Position

We are hiring AI Engineers at the Principal and Senior Principal levels 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.

Requirements

Principal: 12+ years of experience (or 8+ with a Master's degree).
Sr. Principal: 15+ years of experience (or 12+ with a Master's, 8+ with a PhD).
Track record of architecting and shipping complex, enterprise-grade distributed systems and full-stack AI platforms.
Expert Python capabilities plus mastery of additional core languages (Go, Java, Node.js).
Deep expertise in cloud-native microservices (AWS/Azure/GCP) and distributed architecture.
Proven mastery of LLMs (GPT-4, Llama 3, Claude), orchestration (LangChain, LangGraph), multi-agent architectures, and dynamic retrieval pipelines.
Strong evaluation, and fine-tuning/RAG patterns.
Bachelor's, Master's, or PhD in Computer Science or a related field.

Responsibilities

Architect and govern the enterprise Proxy-First AI Ecosystem and unified API strategies, securing total model-vendor independence.
Lead build-vs-buy decisions and establish standard architecture patterns across agentic, RAG, hybrid, and traditional systems.
Spearhead multi-system GenAI transformations across marketing, sales compensation, and quote-to-cash workflows.
Architect advanced reasoning pipelines, knowledge graphs, and autonomous multi-agent networks.
Establish enterprise-wide "LLM as a Judge" evaluation standards and golden datasets.
Design cost and performance optimization engines that dynamically route queries based on task complexity.
Set security standards for AI safety, PII protection, and adversarial defense (keyword filtering, behavioral analysis, adversarial training).
Lead high-ambiguity, cross-team technical initiatives.
Communicate technical visions and business trade-offs directly to executive stakeholders while elevating engineering capabilities across the entire organization.