Artemis is building the future of AI-driven cybersecurity, helping companies defend themselves effectively in an era where AI is fighting AI on the cyber battlefield.

Our platform brings a new approach to the $100B security operations market, building a live model of each customer's environment and using AI agents to detect, investigate, hunt, and respond to threats at machine speed. Just one year after our founding, Artemis is one of the fastest-growing cybersecurity companies of all time, with customers including multiple Fortune 500 companies, Global 2000 enterprises, and AI innovators like Cursor.

We have raised $70M from Felicis, First Round Capital, Theory Ventures, Two Sigma Ventures, Lockstep VC and Brightmind. We are also backed by some of the most prominent operators in cybersecurity, including the CEO of Crowdstrike, the former CEO and CTO of Splunk, and the founders of Abnormal AI and Demisto.

Artemis's founders have built and scaled security products used by tens of thousands of customers. Shachar Hirshberg (CEO) led Amazon GuardDuty, the world's largest cloud detection product, was an early employee at Demisto, the company that invented the SOAR category, was an engineering leader at Palo Alto Networks, and holds an MBA from Harvard. Dan Shiebler (CTO) led all AI and machine learning at Abnormal AI, the pioneer of behavior-based detection, spent five years building analytics using machine learning and vector databases at Twitter, and holds a PhD in machine learning from Oxford.

Our team of software engineers, AI researchers, security engineers, and product designers comes from Google, Meta, AWS, Wiz, CrowdStrike, SentinelOne, Abnormal AI, Perplexity, Bridgewater, Mercor, CERN, and more.

We're growing fast and looking for builders who want to help us serve our rapidly 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 across the team.

Engage with the detection engineering cycle - Partner with the security engineering team to surface patterns from case review, propose new detection ideas, and validate that shipped detections perform as expected in production environments.