Senior AI Engineer (Unit 42)

Our Mission

At Palo Alto Networks®, we're united by a shared mission-to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you're ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you're in the right place.

Who We Are

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That's why most of our teams work from the office full time, with flexibility when it's needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

• Design and implement autonomous agents using frameworks like LangGraph, CrewAI, or AutoGen to automate complex SOC investigation playbooks.
• Build and optimize RAG (Retrieval-Augmented Generation) systems and Vector Databases to provide agents with real-time historical context.
• Transition agents from instruction-following to self-learning through LLM Fine-tuning (LoRA/QLoRA) and RLHF based on analyst decisions.
• Fine-tune models to understand unstructured telemetry, EDR logs, and network traffic, translating noisy data into actionable security narratives.
• Collaborate with SOC teams to codify human intuition into agentic reasoning and robust production deployments.
• Develop evaluation loops to rigorously measure agent accuracy and eliminate hallucinations in high-stakes environments.

• Bachelor's degree with 5 years of experience, or Master's degree with 3 years of experience in a relevant field.
• Deep focus and hands-on experience with LLMs, Prompt Engineering, and Agentic Frameworks.
• Proficiency in Python and experience handling high-volume data streams (e.g., Spark, Kafka, or Snowflake).
• Proven experience building and deploying production-grade AI applications and distributed systems.
• Exceptional ability to work cross-functionally with product, architecture, and security research teams.

• Experience with multi-agent systems (e.g., 'Researcher' vs. 'Decision' agent architectures).
• Background in traditional Software Engineering (DevOps/CI/CD for ML).
• Published research or personal projects in 'AI for Cybersecurity'.
• Experience building enterprise SaaS platforms.
• Familiarity with the MITRE ATT&CK framework, SIEM/EDR logs, and common attack vectors.