We’re Clover Security.
We’re building the future of product security. Our mission is to enable both humans and AI to build secure-by-design software, at scale, without slowing innovation.
We’re backed by $36M from Team8, Notable Capital, and SVCI, and trusted by multiple Fortune 500 companies.
But funding and logos don’t define us. People do.
Our About us page offers a real look at our culture, our values, and the people behind the product.
This is where you come in.
We’re looking for a Security Researcher to join our Research team and drive cybersecurity research at the intersection of Product Security and AI. You'll investigate security risks in modern software development, including AI-assisted and agentic workflows, and translate research into product capabilities, customer guidance, and industry insights.
What you'll do
Conduct deep technical research across codebases, architectures, integrations, data flows, permissions, and agentic workflows to identify product security risks that traditional scanners often miss.
Investigate how AI coding agents, LLM-based workflows, and AI-assisted engineering practices change the way security risks are introduced, missed, prioritized, and remediated.
Turn research into useful outputs, including product recommendations, customer-facing guidance, technical writeups, evaluation ideas, talks, and internal briefs.
Maintain and evolve Clover’s threat-pattern corpus, security context modules, and research-backed detection logic.
Work with product and engineering to translate findings into shipped capabilities, evals, onboarding materials, and go-to-market narratives.
What We’re Looking For
Strong application or product security expertise, with the ability to reason across code, architecture, product behavior, and business context.
A track record of owning research end-to-end: defining questions, doing deep technical work, forming a point of view, and producing useful artifacts.
Strong threat modeling judgment, with experience using frameworks such as OWASP, STRIDE, or similar methodologies to identify and assess common AppSec risks.
Heavy hands-on use of AI coding agents, LLM-based development workflows, or AI-assisted software engineering tools in real-world engineering/research environments.
Strong communication skills, curiosity, independence, and the ability to turn research into outcomes that influence product, engineering, customers, or the market.
If this role excites you - even if you don’t check every box - we’d love to hear from you.