Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified, and real-time view of their security posture. We don’t just provide data; we provide certainty.

We are a $170M Series C-funded category leader. We don’t play in the mid-market; we operate at the highest levels of global enterprise. Today, we are proud to serve 10% of the Fortune 500, protecting global icons such as Apple, Netflix, AT&T, Verizon, and Victoria’s Secret.

As we scale toward our next chapter, we are looking for high-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity.

The Culture Memo: Our Operating System

Safe is not a typical corporate environment. We are a high-intensity, mission-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence.

• Extreme Ownership: We don’t do "not my job." We hire people who see a gap and own the solution from start to finish.

• The Elite Standard: We serve the most sophisticated companies on the planet. Our work must be bulletproof. Whether it’s a line of code or a sales deck, we aim for Tier-1 quality every time.

• Methodology & Rigor: We don’t wing it. From Force Management and MEDDICC in sales to data-driven sprints in engineering, we rely on proven frameworks to stay disciplined and predictable.

• Radical Candor: We move too fast for politics or sugar-coating. We value direct, honest feedback that helps us find the right answer quickly.

• The Series C Hustle: We have the stability of a well-funded leader but the heart of a startup.

The Perks & Ownership:

Core Responsibilities:

• Primary role is to work with the Threat Research team focussing on vulnerability research to analyze affected products and trigger conditions for newly released vulnerabilities

• Utilize vulnerability and exploit intel feeds to identify applicable compensating controls and policies to prevent successful exploitation of these CVEs

• Research various WAF products to identify APIs that provides details about attack surface protected, policies applied and the enforcement status of these policies

• Build automation that continuously monitor changes in these policies and APIs of these WAF solutions

• Setup a lab to apply compensating controls and policies to validate whether that can prevent the exploitation of the CVE in question

• Map and review auto generated mapping of CVEs to compensating controls and policies which feeds back to our CTEM product