Information Security Specialist leading AI-driven detection engineering at TD. Overseeing design and implementation of machine learning–enhanced detections across SIEM/XDR ecosystems.
Responsibilities
lead CTD’s AI-driven detection engineering capability
owns the design, implementation, and operation of machine learning–enhanced detections across SIEM/XDR ecosystems
elevate alert fidelity and analyst productivity through automation, codified pipelines, and governed model lifecycle
partner with CSOC, CSIRT, Threat Hunting, and platform teams to deliver enterprise-scale detections that adapt to evolving threats
mentor L9 engineers and shape CTD’s detection roadmap
Requirements
7+ years in detection engineering, data science for security
proven delivery of production ML detections and MLOps pipelines
deep expertise with SIEM/SOAR/XDR (e.g., Splunk, Sentinel, XSOAR, Microsoft Defender suite) and threat detection methodologies
strong skills in Python (pandas, scikit-learn, PyTorch/TensorFlow), PowerShell, and SQL/KQL
experience with feature engineering, cross-validation, A/B experiments, drift detection, and explainability
familiarity with MITRE ATT&CK, kill-chain and threat modeling practices
demonstrated ability to work across technical and non-technical stakeholders
clear written/spoken communication
experience mentoring engineers and leading cross-functional initiatives
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