Detection Engineering Technical Leader

About the role

This role works within Splunk’s internal security organization as a member of the Detection Engineering team responsible for securing the Splunk portfolio. The role will partner fluidly with peer teams—Threat Hunting & Intelligence, SOC, Advanced Response, and others—to ensure Splunk is prepared for emergent threats. This is a hybrid role that moves dynamically between building scalable detection content, collaborating with incident response organizations, mentoring teammates on detection standards and design patterns, and designing the future of engineering threat detection solutions.

Your Impact

You’ll join a team of engineers focused on securing Splunk’s enterprise and building for the future. Together, you’ll engineer scalable detection systems and automation that power 24×7 monitoring and rapid response to cybersecurity threats. The team sits at the intersection of deep security expertise, strong engineering rigor, and data science:

• Design and build data processing pipelines that efficiently transform high-volume security telemetry into actionable alert signals for downstream agentic and human triage
• Lean into AI/ML to stay ahead of adversaries rather than chasing them
• Drive cross-organizational initiatives with business partners to continuously expand visibility and close detection gaps
• Elevate detection engineers and security content developers through code reviews and technical mentorship
• Hold the team to a standard where engineering excellence is how you work

Minimum Qualifications

• Bachelor’s degree plus 8 years of related experience, or a Master’s degree with 6+ years of related experience, or a PhD plus 3 years of related experience as a Security Engineer, Detection Engineer, Security Content Developer, SOC Analyst, or Security Operations professional
• Deployed and maintained Splunk Enterprise Security content in a production SOC environment, including detections, data models, and data management
• Built detection queries in SPL at scale, including risk-based alerting, statistical baselining, and optimized searches across high-volume data sources
• Integrated AI/ML techniques (e.g., anomaly detection, LLM-assisted workflows) into detection engineering pipelines to reduce false positive rates and accelerate content development
• Translated threat intelligence and ATT&CK-mapped adversary behaviors into detection requirements with defined coverage metrics and measurable success criteria

Preferred Qualifications

• Contributed to collaborative development workflows using Git-based platforms (GitHub, GitLab, or Bitbucket), including branch strategy, code review, and CI/CD integration
• Built or tuned security monitoring coverage across AWS, GCP, or Azure, including native logging services (e.g., CloudTrail, GCS audit logs, Azure Monitor) and cloud-native threat detection
• Tracked and responded to emerging threats and attacker techniques through ongoing research, published work, conference participation, or contributions to detection content
• Wrote production Python (or equivalent) with unit tests, code reviews, and version-controlled deployments in an operational security environment
• Applied statistical methods or ML techniques (e.g., threshold baselining, clustering, anomaly scoring) to security data to improve detection signal quality
• Identified and delivered automation that measurably reduced manual toil or cycle time in detection, triage, or response workflows
• Produced technical documentation, runbooks, or presentations tailored to both engineering and non-technical security stakeholders
• Partnered with SOC, IR, threat intel, and product teams to drive multi-functional detection initiatives from requirement to deployment

This position may perform work that the U.S. government has specified can only be performed by a U.S. citizen on U.S. soil. The successful applicant must be a U.S. Person (i.e., U.S. citizen, U.S. national, lawful permanent resident, asylee, or refugee) and may be required to perform work in FedRAMP High or IL-5 environments.