Product Security Researcher

CAREERS > CTO Office > Product Security Researcher

Product Security Researcher

Tel Aviv, Israel

• Translate real-world security challenges into AI-driven solutions
• Shape prompt strategies and model workflows for security use-cases
• Contribute to AI system development—help architect, prototype, and iterate on models and pipelines
• Design and execute rigorous benchmarks to evaluate the performance of security-focused AI tools
  
  

• Define evaluation frameworks for AI models tackling security tasks
• Build test suites for exploitability analysis (e.g. proof-of-concept generation, severity scoring)
• Measure and report on model accuracy, false-positive/negative rates, and robustness
  
  

• Work with ML engineers to craft and refine prompt templates for security scenarios
• Contribute to model architecture design, fine-tuning, and deployment workflows
• Investigate model behaviors, iterate on training data, and integrate new AI architectures as needed
  
  

• Apply deep knowledge of static and software composition analysis (SAST/SCA)
• Analyze container build pipelines to identify vulnerability origins and remediation paths
• Leverage vulnerability databases (CVE, NVD), threat modeling, and risk assessment techniques
  
  

• Write technical blog posts, whitepapers, and documentation on AI-driven security solutions
• Present findings at internal brown-bags and external conferences
• Mentor teammates on AI security best practices
  
  

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, AI/ML, or related field
• 3+ years in security research, application security engineering
• Hands-on with LLMs, prompt engineering
• Proficient in Python
• Deep understanding of SAST/SCA tools (e.g. SonarQube, Snyk) and their outputs
• Familiarity with container security tooling (Docker, Kubernetes, Trivy)
• Strong data analysis skills for evaluating model outputs and security telemetry
• Excellent written and verbal communication; ability to distill complex topics for diverse audiences
• Collaborative mindset; experience working across research, engineering, and security teams
  
  

• Experience in AI/ML system development—model training, fine-tuning, and production deployment
• Publications or presentations in AI, security, or DevSecOps venues
• Prior work developing open-source security tools or frameworks
• Experience with cloud security services (AWS/Azure/GCP) and infrastructure-as-code scanning
• Familiarity with CI/CD pipelines and MLOps tooling
• Hands-on with fine-tuning workflows