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Artemis

Security Research Engineer

Remote (Remote)fulltimemidAdded today

About this role

Artemis is seeking a Security Research Engineer to drive detection research and AI-powered security automation for cloud and identity environments. You'll conduct threat hunting, build detection tooling, investigate incidents, and work directly with customers to deliver security value in an AI-driven defense platform.

What you'll do

  • Develop AI-powered detection tooling to accelerate detection creation, tuning, and validation
  • Analyze cloud, identity, and SaaS data sources (AWS CloudTrail, Okta, Entra ID) to identify detection opportunities
  • Execute authorized attack simulations to validate detection coverage and identify gaps
  • Proactively hunt for malicious activity across customer environments using the platform
  • Investigate security incidents, refine detection logic, and deliver actionable findings to customers
  • Engage with customers on calls to present analysis, walk through findings, and gather product feedback

What they're looking for

  • Incident response in cloud environments (AWS, Azure, GCP)
  • Identity provider security (Okta, Entra ID)
  • Log-based analysis and threat detection
  • Knowledge of threat actor TTPs (tactics, techniques, procedures)
  • Detection engineering at scale
  • Security tools (SIEM, EDR, SOAR)
  • Technical communication with engineers and customers
  • AI tools and models familiarity

Benefits

  • Remote work opportunity
  • Work on cutting-edge AI-driven security technology
  • Direct customer engagement and impact
  • Collaborate with experienced team from Google, Abnormal AI, Wiz, Meta, AWS, and SentinelOne
  • Backed by First Round Capital and prominent cybersecurity operators
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Artemis

Artemis builds an AI-driven cybersecurity platform that detects and defends against modern threats using large-scale LLM systems and intelligent threat detection. The company is hiring product engineers, security researchers, and ML engineers to develop full-stack customer-facing features, AI-powered security detections, and scalable infrastructure for processing security data.

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Likely interview questions

  • Walk us through a complex incident you investigated—what data sources did you analyze and how did you identify the root cause?
  • Describe your experience building detections at scale. How do you balance detection sensitivity with reducing false positives?
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