Sr Staff AI Engineer

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

1d•$163,200 - $264,000•Onsite

About The Position

The IT Engineering team builds AI-first enterprise systems that power critical business workflows across the company. As a Sr Staff AI Engineer, you will set the technical direction across complex initiatives and define architectural standards for scalable systems. You will tackle ambiguous technical problems, remaining hands-on while multiplying your impact through technical leadership and mentorship. Your work will shape the architecture and AI-native engineering practices used across our broader portfolio of enterprise applications.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Minimum of 8 years of software engineering experience with demonstrated technical leadership across complex, production-scale systems.
Deep expertise in full-stack and distributed systems engineering.
Demonstrated experience setting architecture and technical direction across multiple services, applications, or engineering teams.
Production experience designing and building AI-integrated systems using LLMs, RAG, tool calling, and agentic workflows.
Strong understanding of AI evaluation, guardrails, model reliability, security, latency, and production observability.
Strong understanding of APIs, enterprise data, system integration, cloud-native architecture, and production operations.
Proven ability to translate ambiguous business problems into clear technical architectures and execution strategies.
Track record of establishing technical standards and influencing senior engineers and cross-functional stakeholders.

Nice To Haves

Proficiency in TypeScript, Node.js/NestJS, React, Python, and SQL.
Experience with RAG architectures, vector databases, semantic search, retrieval, and context engineering.
Experience with LangChain/LangGraph, MCP, A2A protocols, and production agentic architectures.
Experience establishing evaluation frameworks, LLM security controls, prompt injection defenses, and input/output validation.
Experience with applied machine learning, data science, predictive modeling, or statistical analysis techniques.
Experience with Docker, Kubernetes, event-driven systems, and modern cloud infrastructure.
Experience using AI-native development environments such as Cursor, Claude Code, or Windsurf in professional workflows.
Experience building reusable enterprise platforms or shared technical capabilities adopted across multiple teams.

Responsibilities

Set architectural vision and technical direction for AI-first enterprise applications and platforms spanning multiple business domains.
Lead the architecture and delivery of complex cross-team systems across full-stack applications, cloud-native services, and applied AI.
Establish reusable engineering standards, reference architectures, and shared capabilities for AI-first systems, including agentic workflows and RAG.
Partner with senior leaders to translate ambiguous, high-impact problems into clear technical strategies and influence broader direction.
Drive AI-native engineering practices and modern development workflows using tools like Cursor and Claude Code to improve velocity.
Mentor senior engineers, raise engineering standards, and multiply technical impact across the broader organization.