AI Security Researcher
WFA Digital Insight
Wizinc’s AI Security Researcher role sits at the intersection of cloud infrastructure and emerging AI risk, a niche that demands both deep security expertise and a curiosity for novel attack surfaces. The team’s mandate is not just to catalogue vulnerabilities but to translate those findings into concrete product capabilities, meaning researchers get to see their work move from proof‑of‑concept to a feature that protects Fortune‑100 customers. What sets this position apart is the emphasis on independent, multi‑quarter investigations and the expectation to communicate findings across product and engineering, requiring strong writing and presentation skills. Candidates should be comfortable scripting in Python or Go, interrogating large telemetry datasets, and thriving in a remote‑first environment that values technical depth over buzzword titles.
Job Description
Come join the organization that is redefining security for the AI era. As one of the fastest-growing startups ever, we enable teams to secure cloud and AI applications by connecting code, cloud, and runtime into a single shared context. Trusted by security teams all over the world, we have a proven track record of success and a culture that values world-class talent. Not to mention, we're now powered by Google, meaning we offer our customers an AI-powered platform that harnesses Google’s Threat Intelligence and Security Operations to better detect, prevent, and respond to threats across all environments, allowing for further innovation.
Our Wizards from all over the globe work together to protect the infrastructure of our customers, including over 65% of the Fortune 100, who trust us to scan and secure over 230 billion files daily. We’re honored to be a leading player in a massive and growing market, and we continue to look for exceptional Wizards who are eager to make a significant impact on our team. At Wiz, you’ll have the freedom to think creatively, dream big, and use your full range of skills to contribute to our momentous growth. Come join our team and help us create secure cloud environments that allow even the best companies to move faster, all while having some fun!
AI Security Researcher
Minimum qualifications:
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5+ years of hands-on experience in security or security research, specifically relevant to modern cloud environments (AWS, GCP, Azure, Kubernetes, etc.).
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Strong hands-on skills with scripting languages (e.g., Python, Go) for automation and research, as well as query languages (e.g., KQL, SQL) for efficient data analysis of security telemetry.
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Proven ability to work independently, prioritize effectively, and drive complex, multi-quarter research projects from initial concept through to clear, delivered impact.
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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.
- Specialised knowledge or research experience in AI security, focusing on risks to AI as deployed in the enterprise.
Preferred qualifications:
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Experience in public-facing work, such as presenting at recognised industry conferences, authoring technical blog posts, or publishing research.
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Experience conducting data-driven research and working with large-scale security telemetry to derive statistically significant or high-impact findings.
About the job:
We're looking for a talented AI Security Researcher to join our team and play a critical role in Wiz's foundational, risk-driven approach to cloud security. This role requires deep technical research into complex cloud- and AI-native environments to identify the most significant, unaddressed risks.
Responsibilities:
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Conduct deep technical research to discover and report novel risks and attack vectors specific to modern cloud- and AI-native architectures and systems.
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Discover and articulate the highest unaddressed risk areas, working with Product and Engineering teams to translate research into product capabilities.
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Define necessary foundational product capabilities by delivering both compelling proofs of risk (demonstrating impact) and technical POCs (showing how to solve it).
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Work closely with Product and Engineering teams to ensure comprehensive risk coverage and support the investigation of new and complex product scope.
By submitting your application, you acknowledge that Wiz will process your personal data in accordance with Wiz's Privacy Policy and that you consent to the retention of your application for consideration for future opportunities at Wiz.
Applicants must have the legal right to work in the country where the position is based, without the need for visa sponsorship. This role does not offer visa sponsorship.
Wiz is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
By submitting your application, you acknowledge that Wiz will process your personal data in accordance with Wiz's Privacy Policy.
How to Stand Out
- Highlight any Python or Go scripts you have written for security automation; include a brief description or link in your résumé.
- Prepare a concise, 5‑minute walkthrough of a past research project that shows the problem, methodology, and impact.
- Bring concrete examples of how you turned raw telemetry data into actionable insights; metrics are optional but clarity is key.
- If you have published work or spoken at conferences, reference those pieces directly in your cover letter.
- Expect interviewers to probe your ability to work independently across long timelines; be ready to discuss project planning and prioritisation.
- When negotiating, focus on equity and professional development budget, as salary ranges are not disclosed.
- Watch for vague expectations around “AI security” – clarify whether the role leans more toward cloud risk or machine‑learning model risk before accepting an offer.
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