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Detection Engineering Technical Leader

Job in Hillsboro, Washington County, Oregon, 97123, USA
Listing for: Webex Events (formerly Socio)
Full Time position
Listed on 2026-09-02
Job specializations:
  • IT/Tech
    Cybersecurity
Job Description & How to Apply Below

Splunk Detection Engineer

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

Meet The Team

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 our multi-functional peer teams:
Threat Hunting & Intelligence, SOC, Advanced Response, and others, to ensure that Splunk is always prepared for emergent threats. This is a true hybrid role. You will move dynamically between building new scalable detection content, collaborating with incident response organizations, mentoring teammates on detection standards and design patterns, as well designing the future of engineering threat detection solutions at Splunk.

Your

Impact

You'll be joining a team of like-minded engineers focused on securing our enterprise and building for the future — together, we engineer scalable detection systems and automation that power 24x7 monitoring operations and rapid response to cybersecurity threats. We sit at the intersection of deep security expertise, strong engineering rigor, and data science: you'll design and build data processing pipelines that efficiently transform high-volume security telemetry into actionable alert signals for downstream agentic and human triage, and we lean hard into AI/ML to stay ahead of adversaries rather than chasing them.

Beyond the technical craft, we drive complex, cross-organizational initiatives with business partners to continuously expand visibility and close detection gaps — working across boundaries to make the whole security program better. We bring our experience to bear through code reviews and technical mentorship, helping elevate detection engineers and security content developers around us, and we hold ourselves to a standard where engineering excellence isn't aspirational...it's

how we work.

Minimum Qualifications:
  • Bachelor's + 8 years of related experience or a Master's degree with 6+ years of related experience, or a PhD + 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 (Git Hub, Git Lab, 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., Cloud Trail, 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
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