Staff Product Security Engineer

How You'll Make an Impact

As our founding Principal Product Security Engineer, you'll work closely with the Head of Security & IT to set and execute the security strategy for the Endor Labs platform. That spans supply chain security, first-party code scanning, runtime monitoring, AI agent hardening, threat modeling and design reviews, along with deploying agents to improve quality and scale in each of these areas.

The top problems you will solve

• Fix issues in our application. AI tooling is good at generating findings. Validating, prioritizing, and fixing findings at scale on an ongoing basis is the new frontier. We are building a platform around this for our customers, and our work internally should guide these efforts.
• Stop insecure code from being merged. You'll help build out our internal apparatus around our own AI SAST product and set up paved paths so everyone, from principal engineers to citizen developers, can be confident in the security of their code contributions.

Both of these are simple in goal, lofty in practice.

Beyond these problems, running application security for an application security company is a rare opportunity to help shape the product we build for customers. Our application security program heavily utilizes our own platform, which makes our program both a proving ground for the product and an incubator for our R&D. You'll work closely with Product and Engineering to solve problems for customers too: shaping the roadmap, reviewing designs and mocks, and giving feedback on implementation. You'll share what works with customers, prospects and the broader security community.

What You Bring to the Table

• 10+ years in application or product security, including staff- or principal-level technical leadership.
• A track record of building security tooling and automation that runs at scale across an engineering organization, and of measuring whether it works.
• A track record of influencing a product or platform roadmap: you've turned internal security work into something other teams or customers adopt.
• Demonstrated hands-on work applying LLMs and agents to security problems. You've built a harness, compared tools, or measured where they fail, and you have well-reasoned opinions on both halves of AI code security: how to find, validate and fix vulnerabilities in existing code, and how best to prevent insecure code from being merged.
• Deep threat modeling and secure architecture skills. You know a strong threat model is one of the biggest levers in AI-driven scanning efforts.
• The ability to set direction and influence senior engineering, product and customer stakeholders without formal authority.
• A fix-it mindset: you investigate, find root causes, and drive remediation rather than just reporting.
• Comfort building from scratch in an ambiguous, fast-moving environment, and setting priorities without an established playbook.

Nice-to-haves

• Experience securing build systems and CI/CD at scale, especially Bazel monorepos.
• A background in security research, such as vulnerability research, program analysis, or static analysis tooling.
• Conference talks, publications, or open-source work in application security.

Show Us Your Work

If you've written about AI security tooling, built a harness, or given a talk, link it in the Website field. We weigh public work more heavily than polished résumés, including work that documents what didn't work.