Threat Detection Researcher (Windows/Linux/MacOS)
$200,000–$250,000 year
On-siteNew York City, New York, United States
Job Summary
Develop detections and tools to protect customers from cloud threats by investigating attacks on cloud environments and malware targeting cloud and AI workloads. Hunt and analyze real-world attacks and emerging cloud and AI threats, then collaborate closely with the R&D team to transform research insights into product features. Work with customers in response to requests related to suspicious activity or potential incidents, while creating best practices and security policies based on research findings. Deliver external-facing content including blog posts and talks at security conferences based on security insights and novel research. This role supports the Wiz Runtime Sensor within a team securing over 230 billion files daily for Fortune 100 companies.
Required Qualifications
- 6+ years of experience in security or threat research in which you conducted deep research with actionable conclusions and impacts
- Intimate knowledge of OS internals (Windows/Linux/MacOS) and networking
- Familiarity with cloud services, Kubernetes, cloud environment architecture, and the major cloud providers (AWS, GCP, Azure)
- Proficiency in Python for tool development and automation
- Experience delivering security detections in customer-facing product(s)
- The ability to learn independently, to be self-driven and goal-oriented
- Excellent communication and teamwork skills
- Applicants must have the legal right to work in the country where the position is based, without the need for visa sponsorship
Desired Qualifications
- knowledge of Go, Rust, or C/C++
- Hands-on experience with malware analysis/reverse engineering/vulnerability research
- Familiarity with notable threat actors and threat intelligence analysis
- IR/red-team/threat-hunting experience
- Experience leveraging AI to supercharge research and detection workflows
- Deep knowledge of modern threat classes (Supply Chain, CI/CD, or threats targeting AI infrastructure and agentic frameworks)
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