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Artemis is seeking a Detection Engineer to own the detection content powering its AI-native security platform. You'll design, build, test, and continuously tune high-fidelity detections across cloud (AWS, Azure, GCP), identity (Okta, Entra ID), endpoint (EDR), and SaaS environments. This is a hands-on engineering role where you treat detection as code, leverage AI as a force multiplier, and ensure every rule shipped directly impacts threat detection quality for customers.
Key responsibilities include building and maintaining a detection library with version-controlled rules and CI/CD deployment; mapping and closing coverage gaps against MITRE ATT&CK; validating detections against real attacks through simulation and testing; tuning false-positive and false-negative rates across the fleet; using AI-assisted workflows to author and test rules at scale; building behavioral and anomaly-based detections that establish baselines of normal activity; engineering detections that produce rich context for autonomous investigation; translating threat intelligence into durable detection logic; and partnering with SOC and research teams to drive continuous improvement.
You'll need 5+ years of hands-on cybersecurity experience with significant detection engineering background. Required skills include proficiency in detection languages (Sigma, KQL, SPL, YARA-L), Python coding, deep knowledge of MITRE ATT&CK, experience with detection-as-code workflows (Git, peer review, CI/CD), and demonstrated ability to use AI tools for detection authoring and validation. Strong log-analysis skills, behavioral/anomaly detection experience, and clear communication are essential. Bonus qualifications include MDR/MSSP/SOC experience, attack simulation frameworks (Atomic Red Team), threat hunting background, UEBA platform experience, and open-source detection contributions.
