Applied Security Researcher

SUMMARY

We're looking for a talented Applied Security Researcher to join our team and play a major role in Wiz's frontier research team, enabling contextual code understanding across complex cloud deployments.

WHAT YOU'LL DO

• Investigate the Code, Cloud, and AI technologies that Wiz integrates with and protects, answering key research questions to unlock new features and product areas.
• Design and build high-quality functional prototypes, driving abstract product ideas from inception into working PoCs and supporting development teams through initial implementation.
• Conduct technical research to model risks and attack vectors specific to modern cloud- and AI-native architectures and systems.
• Define and implement novel agentic workflows and advanced methods to express consistent contextual understanding of evolving application and cloud environments.

WHAT YOU'LL BRING

• 5+ years of hands-on experience in security or security research.
• Strong threat-modeling mindset, with a deep understanding of both how attackers approach complex environments and how enterprises defend them.
• Deep architectural understanding of complex software systems (Low-level, Distributed, or Core System Engineering mindset).
• Proven ability to work independently, prioritize effectively, and drive complex, multi-quarter research projects from initial concept through to working PoC and product integration.
• Strong ability to define and implement agentic workflows. 
• Excellent written and verbal communication skills, with a track record of successfully collaborating with cross-functional teams (e.g Product, Engineering, Marketing) to achieve shared goals.

ADVANTAGE

• Security research experience in modern cloud environments (AWS, GCP, Azure, Kubernetes, etc.).
• Specialized knowledge or research experience in AI security, focusing on risks to AI as deployed in the enterprise.
• Solid foundation in program analysis or programming language theory (e.g., parsing, ASTs, compilation, or static code analysis).
• Familiarity with model benchmarking, evaluation or fine tuning.
• Hands-on experience with query languages (e.g., KQL, SQL) for efficient data analysis of security telemetry, or relevant large-scale data mining experience.