Insider Threat Detection Engineer

🕒 vor 7 Tagen

🏄 California, District of Columbia, +3 weitere Bundesländer – Remote

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💵 $168.000 - $310.500 / Jahr

⏰ Vollzeit

🟠 Senior

🔴 Experte

👷🏻‍♀️ Ingenieur

🦅 H1B-Visum-Sponsor

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👻 Geisterscore 1%

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🗣️🇺🇸🇬🇧 Englisch erforderlich

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Logo of NVIDIA

NVIDIA

10.000+ Mitarbeiter

Gegründet 1993

🏥 Gesundheitswesen

🏭 Fertigung

🤖 Künstliche Intelligenz

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA ist ein führendes Technologieunternehmen mit Spezialisierung auf beschleunigtes Computing und Künstliche Intelligenz (AI). NVIDIA treibt Fortschritte bei Grafikprozessoren (GPUs), Cloud Computing, Rechenzentren und Virtual Reality voran und fokussiert dabei Branchen wie Gaming, Automotive, Gesundheitswesen und Robotik. Innovationen des Unternehmens wie NVIDIA Omniverse transformieren traditionelle digitale Prozesse, indem sie hochrealistische Simulationen und Rendering-Aufgaben ermöglichen. Die Anwendungen erstrecken sich über zahlreiche Branchen – von autonomen Fahrzeugen mit NVIDIA DRIVE über Gesundheitslösungen mit NVIDIA Clara bis hin zu AI-gestützten Analysen und Workflows.

Beschreibung

• Build, test, deploy, and tune detections across identity, endpoint, cloud, SaaS, collaboration platforms, source-code repositories, build systems, removable media, data movement, and employee-lifecycle signals • Lead and support investigations involving unusual data movement, unapproved application use, external sharing, access anomalies, compromised accounts, employee transitions, and other insider-risk scenarios • Collect and correlate information from endpoint, identity, cloud, source-code, collaboration, data-protection, and approved business sources to reconstruct activity and establish timelines • Develop automation, data pipelines, integrations, dashboards, and investigation tools to reduce manual work and improve investigation consistency and efficiency • Operate and improve insider-risk and data loss prevention capabilities by assessing policy performance, detection coverage, alert quality, false positives, and case-management workflows • Use hypotheses, threat models, test cases, version control, peer review, and performance measures to improve detections; work with system owners to address telemetry or control gaps • Present findings distinguishing facts from inferences, including confidence levels, data limitations, alternative explanations, and unanswered questions • Work with authorized partners on evidence preservation, containment, escalation, and remediation while following requirements for scope, access, confidentiality, auditing, and retention • Collaborate with Security, Legal, HR, Privacy, IT, Incident Response, engineering teams, and business partners throughout investigations

🎯 Anforderungen

• Bachelor’s degree in Computer Science, Cybersecurity, Information Security, Data Engineering, or a related field, or equivalent experience • 7+ years of experience in insider threat, detection engineering, security operations, incident response, digital forensics, data protection, threat hunting, or a related security field • Experience conducting security investigations, including defining scope, collecting evidence, developing timelines, analyzing activity, documenting findings, escalating concerns, and applying lessons learned • Experience with SIEM, DLP, UEBA, EDR, insider-risk management, identity security, case management, or security orchestration technologies • Proficiency in at least one programming or scripting language, such as Python, Go, Java, JavaScript, or TypeScript • Experience building automation with APIs, structured data, source control, and testing • SQL, security-query, and data-analysis skills • Knowledge of identity and access management, endpoints, cloud services, collaboration platforms, SaaS integrations, data classification, source-code environments, and data-exfiltration methods • Experience translating insider-risk scenarios into telemetry requirements, detection logic, investigation workflows, controls, test cases, and performance measures • Ability to distinguish indicators from substantiated findings, avoid assumptions about intent, and explain evidence limitations • Clear written and verbal communication and experience working with technical, legal, privacy, HR, and business partners on sensitive matters • Experience engineering insider-risk, data loss prevention, or endpoint data-protection capabilities is valued • Experience with security data pipelines, entity timelines, relationship models, behavioral baselines, or investigator applications is valued • Knowledge of digital forensics, evidence preservation, chain of custody, incident-response coordination, and legal, privacy, and employee-relations requirements is valued

🏖️ Vorteile

• Equity • Benefits

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