Palo Alto Networks
Principal Security Researcher (AI-Assisted Vulnerability Research)
$172K–$278K
Santa Clara, United States of America · No · Principal · Full-time · Posted Sep 15, 2026
- Experience
- 7+ years in vulnerability research, offensive security research, reverse engineering, fuzzing, exploit development, program analysis, security automation, or a closely related security research role.
- Education
- Master's degree in Computer Science, Cybersecurity, or a related technical field, or equivalent practical experience.
- Visa sponsorship
- Immigration sponsorship: Yes
About the job
Designs and builds AI-assisted security research systems to discover, validate, analyze, and report high-impact vulnerabilities in real-world and open-source software.
What you'll do
- Build and improve reproducible AI/security harnesses, evaluation pipelines, and research infrastructure for vulnerability discovery and validation.
- Conduct vulnerability research, including fuzzing, reverse engineering, root-cause analysis, exploitability assessment, patch analysis, and proof-of-concept validation.
- Analyze research outputs and produce validated findings, technical reports, benchmarks, tools, disclosures, or other security artifacts.
What they ask for
- Master's degree in Computer Science, Cybersecurity, or a related technical field, or equivalent practical experience.
- 7+ years of experience in vulnerability research or a closely related security research role.
- Demonstrated ability to independently drive a technical research project from problem formulation through implementation, evaluation, and written results.
- Strong programming skills and demonstrated security research or technical output.
Nice to have
- PhD in a related field, or equivalent demonstrated research experience.
- Experience building AI agent, fuzzing, evaluation, or vulnerability-validation harnesses and workflows.
Pay
$172,100.00 - $278,300.00/yr USD base salary
Tools
LLMs, AI agents, fuzzing, static analysis, dynamic analysis, program analysis, reverse engineering, security automation
AI focus
Uses LLMs and AI agents to build and improve vulnerability-research workflows, including discovery, validation, evaluation, and reporting.
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