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Palo Alto Networks Logo Palo Alto Networks · IT - Software Development

Ai-first Core It Software Engineering: Software, Ml & Data

United States, Santa Clara · Job Posted March 19, 2026
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Job Description

This is a Unified Application for our AI-First IT Transformation portfolio. We recognize that top-tier AI talent often has skills that span multiple domains. By applying here, your profile is evaluated by our core IT strategy team for multiple high-impact leadership and technical roles powering the entire enterprise, ensuring we find the right home for your specific expertise.

Job Responsibility

  • Lead the hands-on development of core Enterprise IT Business software leveraging AI components and LLM infrastructure with both traditional and Generative AI model deployment
  • Build and industrialize agentic AI systems and multi-agent frameworks, ensuring secure and effective use of GenAI technologies at the platform level
  • Design and implement robust foundational data pipelines, perform advanced statistical analysis, and develop new ML models to drive autonomous system behavior
  • Design large-scale, distributed AI/ML systems optimized for low latency, high throughput, and developer-friendliness (Inference optimization)
  • Establish evaluation frameworks to measure AI quality (accuracy, hallucination rates) and overall system reliability across the Enterprise AI Factory

Requirements

  • 3-5+ years of experience in Software Engineering, Data Science, or Machine Learning (Staff level)
  • 6-8+ years (Senior Staff)
  • 8-12+ years (Principal level)
  • Expert-level server-side development (Python, Java, Go) OR deep expertise in statistical modeling, ML algorithms, and LLM fine-tuning
  • Direct experience with RAG architectures, LLM APIs, and Vector Databases (e.g., Pinecone, Milvus)
  • Hands-on experience with Kubernetes, CI/CD, and distributed systems for large-scale AI deployment

Nice to have

  • Experience with multi-turn dialogue management, Text-to-SQL systems, and causal inference
  • Understanding of adversarial defense and security principles as they apply to AI model integrity
  • PhD or Master’s in Computer Science, Applied Mathematics, or Machine Learning
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