NVIDIA Security is seeking a Senior Detection Engineer to join the Detection and Automation Engineering team. On this team, we build reliable detection coverage that helps responders identify real threats quickly, reduce unnecessary noise, and protect NVIDIA's enterprise, cloud, developer, AI, and production environments. Do you enjoy turning sophisticated security signals into detections responders can trust? Can you read an incident write-up, a red-team result, or an unusual authentication pattern and decide what is worth alerting on? We want someone who can move from hypothesis to tested production content and explain the tradeoffs clearly.
We work closely with incident response, threat intelligence, security operations, cloud security, and engineering teams. We protect enterprise, cloud, identity, endpoint, collaboration, developer, AI, and production environments. We care about detections that are explainable, measured, maintainable, and useful during real investigations.
What You'll Be Doing:
Build and tune high-confidence detections across platforms such as Splunk, Microsoft Sentinel / Defender, CrowdStrike, cloud-native logs, identity telemetry, endpoint data, SaaS platforms, and developer systems.
Translate incidents, hunts, threat intelligence, red-team findings, and vulnerability context into detection logic we can test and operate.
Investigate real telemetry before we alert on it, including field behavior, timing, joins, baselines, and the false positives a responder will actually see.
Drive the full detection lifecycle: design, query development, validation, peer review, documentation, deployment, tuning, monitoring, and retirement.
Strengthen detection-as-code workflows, including test data, quality checks, metadata, rollout safety, coverage tracking, and detection health reporting.
Partner with responders to cut noise, add useful context, improve severity decisions, and build follow-up detections after investigations.
Shape logging, normalization, enrichment, and retention requirements when the telemetry we need is missing or hard to use.
Coach analysts and engineers through design reviews, query reviews, and clear guidance on what makes a detection credible.
What We Need to See:
8+ years of experience in detection engineering, security engineering, threat hunting, incident response, SOC engineering, or information security monitoring.
A degree in Computer Science, Cybersecurity, Engineering, or equivalent experience
Hands-on experience building and tuning detections in a major SIEM or security analytics platform.
Strong query and scripting skills, especially SPL, KQL, SQL, Python, or similar languages used to analyze security telemetry and automate repetitive work.
Practical understanding of attacker behavior across identity, endpoint, cloud, network, email, collaboration tools, developer infrastructure, secrets, and data theft.
Ability to move from raw logs to a production-ready detection, including field semantics, thresholds, joins, baselines, false positives, missing data, and triage context.
Comfortable working with Git, code review, automated checks, CI/CD, documentation, and operational ownership of the content you ship.
Clear communication and sound judgment. You should be able to explain why a detection matters, what it misses, what we should do next, and when we should choose not to alert.
Ways to Stand Out From the Crowd:
You have led or materially improved a detection-as-code program across more than one security platform.
Background in cloud, identity, Kubernetes, CI/CD, supply-chain, or AI-tooling attack paths well enough to design detections without waiting for a complete recipe.
Detected abuse in developer systems, package ecosystems, secrets workflows, AI coding tools, agents, bots, or model-serving infrastructure.
Worked closely with incident response, threat hunting, red team, purple team, malware analysis, or forensics teams.
Built validation methods such as replay tests, synthetic telemetry, attack emulation, detection unit tests, or coverage reporting.
168,000 USD – 270,250 USD for Level 4; and 196,000 USD – 310,500 USD for Level 5.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 8+ years of experience in detection engineering, security engineering, threat hunting, incident response, SOC engineering, or information security monitoring
- Degree in Computer Science, Cybersecurity, Engineering, or equivalent experience
- Hands-on experience building and tuning detections in a major SIEM or security analytics platform
- Strong query and scripting skills, especially SPL, KQL, SQL, Python, or similar languages
- Practical understanding of attacker behavior across identity, endpoint, cloud, network, email, collaboration tools, developer infrastructure, secrets, and data theft
- Ability to develop production-ready detections from raw logs, including field semantics, thresholds, joins, baselines, false positives, missing data, and triage context
- Experience with Git, code review, automated checks, CI/CD, documentation, and operational ownership
- Clear communication and sound judgment in explaining detection value, limitations, next steps, and alerting decisions
- Experience leading or materially improving a detection-as-code program across multiple security platforms
- Background in cloud, identity, Kubernetes, CI/CD, supply-chain, or AI-tooling attack paths
- Experience detecting abuse in developer systems, package ecosystems, secrets workflows, AI coding tools, agents, bots, or model-serving infrastructure
- Experience collaborating with incident response, threat hunting, red team, purple team, malware analysis, or forensics teams
- Experience building replay tests, synthetic telemetry, attack emulation, detection unit tests, or coverage reporting
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
