Insider Threat Detection Engineer

Job not on LinkedIn

🔥 0 minutes ago

🏄 California, District of Columbia, +3 more states – Remote

🏄 California – Remote 🏛️ District of Columbia – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $168k - $310.5k / year

⏰ Full Time

🟠 Senior

🔴 Lead

👷🏻‍♀️ Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• Equity • Benefits