Palo Alto Networks
Sr Staff IT AI Software Engineer
$145K–$236K
Office - USA - CA - Headquarters · No · Senior Staff · Full-time · Posted Aug 3, 2026
- Experience
- Minimum of 9 years of related experience with a Bachelor's degree; the posting also allows equivalent military experience. Separately, 9+ years of professional Python backend development experience.
- Education
- Bachelor's degree in Computer Science or a related field, or equivalent military experience.
- Visa sponsorship
- Immigration sponsorship: Yes.
About the job
Leads architecture and delivery of scalable enterprise software and AI-native services, including agentic workflows, LLM evaluation, retrieval, security, and full-stack applications.
What you'll do
- Set architecture and deployment strategy for scalable software, agentic systems, retrieval pipelines, and MCP servers.
- Establish AI evaluation, prompt engineering, and LLM security standards, and ensure enterprise-grade quality and performance.
- Partner with executives and cross-functional teams, lead project outcomes, and mentor engineers.
What they ask for
- 9+ years of professional backend development experience with Python, including Django or FastAPI and fault-tolerant microservices.
- Experience architecting, deploying, and scaling production-grade Generative AI and LLM applications, including agentic frameworks, RAG, guardrails, and evaluation workflows.
- Frontend expertise with JavaScript, TypeScript, and React.
- Expert-level Docker and Kubernetes (GKE) proficiency; track record delivering enterprise-grade software at scale.
Nice to have
- Hands-on Google Cloud Platform, especially Google Vertex AI; Agent SDK, LangChain, LangGraph, A2A protocols, or MCP servers.
- Experience scaling Agentic IDEs such as Cursor or Windsurf; Master's degree or PhD in Computer Science or a related field.
Pay
$145,000.00 - $235,500.00/yr USD base salary
Tools
Python, Django, FastAPI, React, Google Cloud Platform, Vertex AI, LangChain, Kubernetes (GKE)
AI focus
Leads development of production-grade Generative AI and LLM applications, agentic systems, RAG and retrieval pipelines, AI evaluation, prompt engineering standards, LLM security, and MCP server adoption.
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