AI / Systems Engineer, Offensive Cybersecurity

Zealotlabs

Washington (District of Columbia)

On-site

USD 160,000 - 250,000

Full time

14 days+

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Job summary

Zealotlabs is seeking an AI / Systems Engineer for Offensive Cybersecurity to create AI-driven systems for vulnerability research. Located in Washington, D.C., this role requires deep low-level systems experience and a strong builder mindset. The ideal candidate will work collaboratively with vulnerability researchers and own problems end-to-end. Competitive compensation ranges from $160K to $250K with equity opportunities. Full relocation support is provided for qualified candidates who are willing to work on-site.

Qualifications

  • 2+ years of engineering experience or open to exceptional new grads.
  • Deep low-level systems experience required.
  • Willingness to work in person 5 days per week.

Responsibilities

  • Build production systems for AI-driven vulnerability research.
  • Optimize systems end-to-end from architecture to production.
  • Partner with teams to automate cyber operations.

Skills

Deep low-level systems experience
Strong builder mindset
Comfort with ambiguity
Ability to work end-to-end

Education

2+ years engineering experience or exceptional new grad

Job description

Zealot is deploying AI systems at the center of western cyber operations , backed by tier-1 US VCs and industry leaders. Our team includes alumni of Anthropic, xAI, NSA, USCYBERCOM, Anduril, 8200, and the Mossad. Soon live with the U.S. Department of War and close U.S. allies abroad.

Compensation 160K-250K + 0.25%-0.75% equity

Location Washington, DC On Site

Stage Early-stage startup backed by tier 1 investors. Small, growing team with exceptionally high ownership.

APPLIED AI SYSTEMS KERNEL LOW-LEVEL
  • + Build production systems that conduct AI-driven vulnerability research and exploit development at scale.
  • + Work close to the metal: operating system internals, kernel-level interfaces, and low-level performance optimization.
  • + Own problems end-to-end across architecture, implementation, and shipped production code.
  • + Partner directly with vulnerability researchers, security operators, and the engineering team to convert manual cyber operations into automated, repeatable systems.
  • + Help define the standards and operating cadence of a team that intends to set the bar for AI-native offensive cyber.
  • + 2+ years of engineering experience. Open to exceptional new grads with demonstrated low-level systems work.
  • + Deep low-level systems experience: operating system internals, kernel work, runtime detection, dynamic analysis, dynamic interception, or comparable. This is non-negotiable.
  • + Strong builder mindset. Comfortable owning systems end-to-end and shipping production code where performance and correctness matter.
  • + Comfort with ambiguity and uncertainty. The most important cultural requirement.
  • + Willing to be in person in Washington, D.C., 5 days per week. Full relocation support provided.
  • + Eligible for the security clearances and customer requirements associated with U.S. government work.
Nice to Have
  • + Vulnerability research, CTF, or prior offensive security experience.
  • + Prior YC company as founder or early engineer.
  • + Engineering experience at xAI, Anthropic, Scale, Palantir, or similar high-bar AI companies.
  • + Open-source contributions to OS-level tooling.
  • + Cyber or security startup engineering experience, especially runtime detection, dynamic analysis, or operating system tooling.
  • + Exposure to ML/AI systems work.
  • + A low-level systems builder first. The non-negotiable is fluency close to the metal; speed is the team's defining operating value.
  • + Comfortable owning problems end-to-end, optimizing for real hardware, and shipping production systems where performance and correctness matter.
  • + Building something massive matters more to you than comfort, titles, or predictability.
  • + You want to be early at a company that will change an industry, and you're ready to do what that actually takes.

Ready?

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