AI Security Researcher: LLM Post-Training & Evaluations

Palo Alto Networks; California (MO); Hybrid; USD 163,000 - 264,000; Full time

Job summary

Palo Alto Networks is seeking a Principal AI Researcher to advance cybersecurity capabilities of large language models and autonomous AI agents. You will develop high-quality security data, realistic training/evaluation environments, graders, and post-training methods across vulnerability research, threat analysis, detection, investigation, remediation, secure coding, and autonomous workflows.

You will collaborate with Security Researchers, ML Engineers, and product teams to move research into

Qualifications

• Strong hands-on experience in cybersecurity areas (vulnerability research, secure coding, threat detection, malware analysis, incident investigation, reverse engineering, fuzzing, or security automation).
• Practical experience developing or evaluating LLM-based cybersecurity systems, source code, software engineering, or tool-using agents.
• Experience designing datasets, benchmarks, graders, evaluation frameworks, or tasks with verifiable outcomes.
• Experience with post-training or model-adaptation methods (supervised fine-tuning, preference optimization, RL, reward modeling, distillation).
• Strong programming skills in Python and at least one system language (C, C++, Rust, Java, or Go).
• Experience with large codebases, security tools, testing frameworks, build systems, debuggers, and containerized environments.
• Strong understanding of experimental design, failure analysis, regression testing, and quantitative evaluation.
• Ability to independently drive ambiguous research problems from investigation through implementation and validation.

Responsibilities

• Design reproducible training and evaluation environments for complex cybersecurity tasks (vulnerability research, threat analysis, detection, investigation, remediation, secure coding, autonomous security workflows).
• Transform source-code repositories, vulnerabilities, security incidents, malware samples, threat intelligence, detection logic, patches, test harnesses, and security tools into structured tasks for LLMs and AI agents.
• Develop high-quality security datasets, including synthetic data, hard negatives, adversarial examples, annotations, and model-generated trajectories.
• Build reliable graders, verifiers, and reward signals using tests, runtime behavior, security-tool outputs, and validation methods.
• Design evaluations for security reasoning, code understanding, threat analysis, root-cause analysis, tool use, long-horizon execution, and autonomous task completion.
• Analyze model failures, data quality issues, grader weaknesses, and reward hacking.

Skills

Cybersecurity research

LLM cybersecurity

Datasets & benchmarks

Post-training methods

Python

System languages

Codebases & security tools

Experimental design

Education

BS/MS in CS or related field

Tools

Containers

Job description

Palo Alto Networks is seeking a Principal AI Researcher to advance cybersecurity capabilities of large language models and autonomous AI agents. You will develop high-quality security data, realistic training/evaluation environments, graders, and post-training methods across vulnerability research, threat analysis, detection, investigation, remediation, secure coding, and autonomous workflows.

You will collaborate with Security Researchers, ML Engineers, and product teams to move research into