Detection Engineering & Content Development
● Design, develop, and deploy advanced detection rules and logic across SIEM, EDR, CSPM, and cloud-native security platforms.
● Build and maintain detection-as-code using modern frameworks and version control systems (Git).
● Create high-fidelity, low-noise detections mapped to the MITRE ATT&CK framework, focusing on cloud-specific threats and techniques.
● Continuously research emerging threats, TTPs (Tactics, Techniques, and Procedures), and translate threat intelligence into actionable detection content.
● Perform detection efficacy testing and validation using purple team exercises and adversary emulation frameworks.
AI & Machine Learning Integration
● Leverage AI/ML capabilities within security platforms to enhance threat detection accuracy and reduce false positives.
● Build and tune machine learning models for anomaly detection, behavioral analytics, and predictive threat identification.
● Integrate generative AI and large language models (LLMs) to accelerate alert triage, investigation workflows, and threat analysis.
● Evaluate and implement AI-powered security tools for automated threat detection, alert enrichment, and investigation assistance.
● Monitor and optimize AI/ML model performance, addressing data quality, model drift, and false positive/negative rates.
Cloud Security Detection & Monitoring
● Act as a Subject Matter Expert (SME) for cloud security detection engineering across AWS, Azure, and GCP environments.
● Design detections leveraging cloud-native logs (CloudTrail, Azure Activity Logs, GCP Audit Logs) and security services (GuardDuty, Security Command Center, Defender for Cloud).
● Build detections for cloud-specific threats including misconfigurations, identity compromise, data exfiltration, and infrastructure attacks.
● Monitor container and Kubernetes environments, developing detections for runtime threats and supply chain attacks.
Security Automation & Orchestration
● Design and implement automated detection deployment pipelines using secure CI/CD methodologies.
● Build custom scripts (Python, PowerShell, Bash) for automated alert enrichment, evidence collection, and response actions.
● Develop and maintain automated response playbooks in SOAR platforms to handle detection-triggered workflows.
● Integrate security tools via APIs to create seamless, automated detection and response ecosystems.
● Identify opportunities to apply automation and AI to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR).
Continuous Improvement & Collaboration
● Analyze detection performance metrics, false positive rates, and coverage gaps to drive continuous improvement.
● Collaborate with threat intelligence, incident response, and threat hunting teams to refine detection strategies.
● Create and maintain comprehensive documentation for detection logic, tuning procedures, and operational runbooks.
● Provide technical guidance on detection engineering best practices and emerging technologies.
● Stay current with the latest security research, adversary techniques, and AI/ML
advancements in cybersecurity.