Role at a glance
- Salary
- $168K – $310.5K/yr
- Location
- 3 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years of experience in detection engineering, security engineering, threat hunting, incident response, SOC engineering, or...
- Education
- A degree in Computer Science, Cybersecurity, Engineering, or equivalent experience
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Role Summary
The Detection and Automation Engineering team builds reliable, explainable detection coverage across NVIDIA's enterprise, cloud, developer, AI, identity, endpoint, collaboration, and production environments. The Senior Detection Engineer turns incidents, threat intelligence, hunts, red-team findings, and security telemetry into tested production detections that help responders identify threats and reduce noise.
What You'll Do
- Build and tune high-confidence detections across SIEM, security analytics, cloud-native, identity, endpoint, SaaS, and developer platforms
- Translate incidents, hunts, threat intelligence, red-team findings, and vulnerability context into testable detection logic
- Investigate telemetry, including field behavior, timing, joins, baselines, and false positives, before deploying alerts
- Drive the detection lifecycle from design and query development through validation, review, deployment, tuning, monitoring, and retirement
- Strengthen detection-as-code workflows with test data, quality checks, metadata, rollout safety, coverage tracking, and detection health...
- Partner with responders and engineering teams to reduce noise, improve context and severity decisions, and shape logging and telemetry...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required experience building and tuning detections in a major SIEM or security analytics platform; strong SPL, KQL, SQL, Python, or similar query and scripting skills; understanding of attacker behavior across identity, endpoint, cloud, network, email, collaboration tools, developer infrastructure, secrets, and data theft; experience with Git, code review, automated checks, CI/CD, documentation, and operational ownership.
Required
- 8+ years of experience in detection engineering, security engineering, threat hunting, incident response, SOC engineering, or...
- 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...
- Practical understanding of attacker behavior across identity, endpoint, cloud, network, email, collaboration tools, developer...
- Ability to move from raw logs to a production-ready detection, including field semantics, thresholds, joins, baselines, false positives,...
- Comfortable working with Git, code review, automated checks, CI/CD, documentation, and operational ownership of the content you ship
- Clear communication and sound judgment
Preferred
- 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
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.