About The Role

Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build.

We're looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion's cloud-native environment. You'll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion.

You'll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what's needed next.

We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters

What You'll Achieve

• Build and tune high-signal detections across cloud, identity, endpoint, and SaaS environments, with review and mentorship from senior teammates as you ramp up.
• Contribute to the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety.
• Build tooling and automation that speed up triage, enrichment, investigation, and detection authoring, including LLM-based workflows where useful.
• Turn threat intelligence and adversary TTPs into detections, telemetry requirements, and response improvements.
• Take part in investigations, incident response, and postmortems, and help turn what we learn into lasting fixes.
• Help define and track metrics such as coverage, MTTD, and alert quality.
• Join a shared on-call rotation for incident response.

Skills You'll Need to Bring

• We're hiring across a range of experience levels. If you have some of these skills but not all, we'd still like to hear from you.
  
  • 3+ years of experience in detection engineering, security operations, incident response, threat hunting, or a closely related security or software engineering role.
  • Have written or tuned detections that run in production, and care about signal quality and cutting noise.
  • Working knowledge of at least one detection or query language (Sigma, KQL, SPL, YARA-L, EQL, or Panther), or strong SQL or Python skills and the drive to learn one quickly.
  • An understanding of how attackers operate (for example, MITRE ATT&CK), and the ability to use it to decide what to detect.
  • Hands-on experience with AWS, GCP, or Azure, ideally including identity and access logs.
  • Have used SIEM, EDR, or SOAR tools in any size of environment.
  • Write clearly in runbooks, design docs, and incident notes, and can own well-scoped projects end to end.

Nice to Have

• Have led purple team, blue team, or adversary emulation exercises that improved detections or telemetry.
• Experience running SIEM, EDR, or SOAR platforms at large scale.
• Experience building or maintaining detection-as-code workflows (version control, CI, and tests for detections).
• Experience applying LLMs or agent-style tooling to security workflows.
• Experience securing AI-enabled systems or endpoint tooling.
• Kubernetes or container detection experience.
• Background in threat intelligence, malware analysis, or digital forensics.
• Contributions to the security community through research, tooling, CTFs, or talks.
• Experience at a high-growth startup or AI company.

Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role's scope and complexity, and the candidate's experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $185,000 - $280,000 per year.

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A Note on AI

You don't need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement - when that's the case, we'll say so explicitly in the qualifications. People who thrive here don't treat AI as a novelty. They use it to think better, and make their work easier for others to build on.