Senior Security Engineer, Detection Engineering

NVIDIA; United States; Remote; USD 168,000 - 311,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior Detection Engineer to join the Detection and Automation Engineering team to build reliable detections across enterprise, cloud, AI, and production environments. You will translate incidents into production-ready detection logic and drive the full detection lifecycle with cross-functional partners.

Ideal candidates bring 8+ years of relevant experience, strong SPL/KQL/Python skills, and hands-on SIEM work.

Qualifications

• 8+ years in detection/security engineering, threat hunting, IR, SOC engineering, or SIEM 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 (SPL, KQL, SQL, Python, or similar).
• Understanding attacker behavior across identity, endpoint, cloud, network, email, and developer tools.
• Ability to move from raw logs to production-ready detections with proper thresholds and baselines.
• Comfortable with Git, code reviews, CI/CD, documentation, and ownership of content shipped.
• Clear communication and sound judgment about when to alert and what it means.

Responsibilities

• Build and tune high-confidence detections across platforms (Splunk, Sentinel, CrowdStrike, cloud logs, identity telemetry, endpoints, SaaS, dev systems).
• Translate incidents, hunts, intel, red-team results into testable detection logic.
• Investigate telemetry before alerting, including field behavior, timing, joins, baselines, and FPs.
• Lead the full detection lifecycle: design, query development, validation, peer review, deployment, tuning, and retirement.
• Strengthen detection-as-code workflows: test data, quality checks, metadata, rollout safety, coverage, health reporting.
• Partner with responders to reduce noise and provide actionable context.
• Shape logging/normalization/retention requirements when telemetry is missing or hard to use.
• Mentor analysts and engineers through design reviews and guidance on detection credibility.

Skills

Detection engineering

SPL/KQL/SQL/Python

Git/CI-CD

Threat hunting

Incident response

Threat intelligence

Communication

Incident write-ups & red-team

Education

B.S. in CS/Engineering or equivalent

Tools

Splunk

Microsoft Sentinel

CrowdStrike

Cloud-native logs

Job description

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.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
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.

Applications for this job will be accepted at least until November 8, 2026.

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.