lever
AI Detection Engineer - SOC Analyst IV
Saviynt
Bengaluru, IND
Full-time
Senior · 8–12 years experience
Hybrid
Discovered 1 weeks ago
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Role Overview
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.
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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.
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