Security Analyst at Artemis

Artemis is building the future of AI-driven defense - helping companies detect and defend themselves effectively in an era where AI is fighting AI on the cyber battlefield. We're backed by First Round Capital, Brightmind, and a group of the cybersecurity industry's most prominent Operators. Our founders, Shachar (ex-Palo Alto Networks, AWS, Demisto) and Dan (ex-Abnormal Security, Twitter) have previously built, launched, and scaled cybersecurity products loved and trusted by tens of thousands of customers, and have the customer, technology, and security know-hows to deliver this vision. Our exceptionally strong team includes software engineers, AI researchers, security engineers, and product designers hailing from Google, Abnormal AI, Wiz, Meta, AWS, CERN, SentinelOne, and more. We are growing our team and looking for passionate builders to join us and support our expanding customer base. Job Overview We're looking for a Security Analyst to be at the core of what we do: reviewing real security cases across customer environments, recommending outcomes, and continuously improving the detection logic that powers our platform. This role sits at the intersection of hands-on SOC work and modern AI-assisted security operations — you'll develop deep expertise in cloud, identity, and SaaS threats while directly shaping the detection content and investigation workflows that protect our customers. Responsibilities Review and triage security cases - Investigate alerts and cases surfaced by the Artemis platform across cloud, identity, endpoint, and SaaS environments. Analyze the underlying logs and evidence to determine whether activity is malicious, benign, or a false positive. Recommend and document case outcomes - Provide clear, well-reasoned verdicts (true positive, false positive, benign confirmed) with supporting evidence and written justifications that feed directly into customer-facing reports and product improvement loops. Build and refine detections - Write new detection logic and tune existing rules to improve signal quality. Work directly in the detection layer to reduce noise, close coverage gaps, and surface threats that matter. Fix and maintain the detection library - Identify misfiring or noisy detections through case review and fix them. Own the quality of the detection content you touch from initial triage through to shipped improvement. Conduct threat hunting - Proactively investigate customer environments for signs of attacker activity that automated detections may have missed, using both structured hypothesis-driven hunting and AI-assisted workflows. Investigate security incidents - Perform deeper triage on escalated or complex cases, piecing together attacker timelines and identifying lateral movement, persistence, or exfiltration across data sources. Contribute to investigation playbooks - Document investigation techniques, artifact patterns, and case patterns as structured playbooks that help scale consistent, high-quality analysis acr