AI Detection Engineer

Saviynt's AI-powered identity platform manages and governs human and non-human access to all of an organization's applications, data, and business processes. Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs. Built for the AI age, Saviynt is today helping organizations safely accelerate their deployment and usage of AI. Saviynt is recognized as the leader in identity security, with solutions that protect and empower the world’s leading brands, Fortune 500 companies and government institutions. For more information, please visit www.saviynt.com.

About the Job
We are building a next-generation Agentic Security Operations Center (SOC) designed for the AI era. We believe that effective security operations must evolve beyond traditional reactive methods. We are building an intelligent, AI-driven SOC that combines deep cloud security expertise with advanced automation and machine learning to predict, prevent, and neutralize advanced threats faster than ever.

We are seeking a SOC Detection Engineer - Cloud and AI Automation to serve as a technical expert responsible for designing, building, and optimizing detection capabilities across our cloud-native security stack. This is a hands-on-keyboard role for someone who thrives on creating intelligent detections, leveraging AI/ML for threat identification, and building automation that scales security operations. You will be responsible for engineering detection logic, fine-tuning AI-powered alerts, and driving continuous improvement in our detection and response capabilities.

WHAT YOU WILL BE DOING

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.