AI Researcher

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 an AI Researcher to join our Research team and play a key role in shaping our AI-native cybersecurity platform. In this role, you’ll investigate product behavior, evaluate AI agent performance, and uncover insights that directly improve the intelligence, reliability, and impact of our systems.

Requirements:

What You’ll Do

• Investigate AI agent outputs, product behavior, customer use cases, and cybersecurity workflows to identify patterns, failure modes, edge cases, and improvement opportunities.
• Design evaluations, metrics, benchmarks, and analysis frameworks that measure AI system quality, consistency, accuracy, and impact over time.
• Translate qualitative and quantitative findings into clear research insights and recommendations for product, engineering, AI development, and customer-facing teams.
• Build internal tools, scripts, automations, and workflows that make research, evaluation, and analysis more scalable and repeatable.
• Work closely with internal partners and customers to turn research insights into meaningful product improvements.
  
  

• 3+ years of experience in data analysis, research analytics, product analytics, AI evaluation, or a similar analytical role.
• Strong analytical skills, including experience working with large datasets, defining metrics, building evaluation frameworks, and investigating complex system behavior.
• Proficiency with SQL and Python (or similar tools) for data analysis, automation, experimentation, and research workflows.
• Experience working with AI tools, LLMs, machine learning-driven products, or evaluation pipelines.
• Strong communication and collaboration skills, with the ability to turn ambiguous questions into actionable insights and work effectively across product, engineering, research, and customer-facing teams.
• Interest in cybersecurity, secure software development, product security, or AI safety and reliability.