Sr/Staff AI Engineer

Palo Alto Networks IT Engineering is seeking a Sr/Staff AI Engineer to design and deliver AI-first enterprise applications and to advance how modern AI capabilities are applied across enterprise software. The role emphasizes scalable architectures and turning business problems into durable technical solutions.

Location

Santa Clara, CA (onsite)

Role Summary

In this position, you will architect and deliver production-ready AI-first enterprise applications across full-stack systems, cloud-native services, and applied AI. You will also help establish engineering practices for AI evaluation and responsible deployment, including guardrails, security, observability, reliability, latency, and cost management.

Responsibilities

• Architect and deliver production AI-first enterprise applications across full-stack systems, cloud-native services, and applied AI.
• Design agentic and retrieval-based systems using LLMs, RAG, embeddings, tool calling, and multi-step workflows.
• Establish robust practices for AI evaluation, guardrails, security, observability, reliability, latency, and cost management.
• Translate ambiguous business problems into scalable technical architectures and drive complex initiatives through production.
• Build reusable engineering patterns and shared capabilities that apply across multiple applications and development teams.
• Drive AI-native engineering practices using tools such as Cursor and Claude Code, while mentoring engineers and raising technical standards.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Senior: 5+ years of software engineering experience (or 3+ with a Master’s degree).
• Staff: 8+ years of software engineering experience (or 6+ with a Master’s degree, or 3+ with a PhD).
• Strong full-stack and distributed systems engineering experience, with demonstrated ownership of complex production systems.
• Production experience designing and building AI-integrated systems using LLMs, RAG, embeddings, tool calling, or agentic workflows.
• Experience with AI orchestration, retrieval, evaluation, guardrails, human-in-the-loop workflows, and production observability.
• Strong understanding of APIs, enterprise data, cloud-native architecture, security, reliability, and production operations.
• Proven ability to translate ambiguous problems into clear technical architectures and influence technical direction.

Technologies

• LLMs, RAG, embeddings, tool calling
• Cursor, Claude Code, TypeScript, Node.js, NestJS, React, Python, SQL
• Vertex AI, LangChain/LangGraph, MCP, A2A protocols
• Vector databases, semantic search, context engineering
• Docker, Kubernetes, event-driven systems
• Windsurf

Compensation

• Base salary range: $144,200.00 - $233,200.00/yr (non-sales roles)
• Compensation depends on qualifications, experience, and work location.
• The offered compensation may also include restricted stock units and a bonus.

Compensation note: For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales-commissioned roles) is expected to align with the annual range listed above.

Education

Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).

Visa and Work Authorization Note

The Company will consider applicants with current work authorization and those who require a transfer of an existing H-1B visa. The Company is not currently considering applicants who require new visa sponsorship (including new H-1B petitions) or individuals currently in OPT/CPT status who will require future sponsorship to maintain work authorization.

Preferred Qualifications

• Proficiency in TypeScript, Node.js/NestJS, React, Python, and SQL.
• Experience with Vertex AI, LangChain/LangGraph, MCP, A2A protocols, or similar AI platforms and frameworks.
• Experience with vector databases, semantic search, context engineering, LLM evaluation, and AI security controls.
• 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 engineering workflows.
• Experience building reusable enterprise platforms or shared technical capabilities adopted across multiple teams.