Senior Staff AI Security Engineer

Team Overview

Platform Security Core builds foundational security infrastructure and AI-driven detection systems for enterprise-scale operations. Our mission is to make security proactive, intelligent, and seamlessly integrated into the ServiceNow platform. We are looking for a hands-on Senior Staff Engineer (Technical Leader) with deep expertise in machine learning systems, inference engines, and security architecture to lead next-generation AI security initiatives.

Role Summary

As a Senior Staff AI Security Engineer, you will architect and deliver enterprise-scale AI security solutions that integrate machine learning, reasoning engines, and real-time inference into core security systems. You will bring strong technical leadership, hands-on machine learning depth, and the ability to design and operate intelligent security systems that learn and adapt.

What You Get to Do in This Role

• Design and implement ML-driven security systems: Build machine learning algorithms for identity risk assessment, anomalous access detection, malware classification, and sensitive data discovery, applying agent guardrails, correlation from telemetry to detect misuse or malicious intent.
• Build inference engines and reasoning systems: Architect high-performance inference pipelines and contextual reasoning systems that apply models in real-time across distributed security decisions.
• Integrate AI into access control and identity: Apply machine learning to access control decisions—contextual analysis, adaptive authentication, behavioral biometrics, and identity confidence scoring.
• Develop attack detection and threat classification: Build ML models for malware detection, anomaly detection, and threat pattern recognition with focus on false-positive reduction, operational efficiency, precision and recall scores.
• Implement sensitive data detection and classification: Design AI systems for PII detection, data classification, and sensitive information governance at scale.
• Lead complex technical initiatives: Provide technical leadership for multi-quarter efforts that combine ML research, systems engineering, and security domain expertise.
• Architect modular, reusable ML systems: Build ML platforms, feature engineering frameworks, and model management infrastructure that teams can adopt and extend.
• Operate production AI systems: Design for observability, model performance monitoring, retraining workflows, and safe model deployment in security-critical environments.
• Collaborate across security and infrastructure: Work with teams across identity, access control, threat detection, and infrastructure to integrate AI solutions end-to-end.
• Research and evaluate emerging AI techniques: Stay current with advances in AI/ML—transformer models, reasoning engines, retrieval-augmented generation—and evaluate their applicability to security problems.

Department: Engineering, Infrastructure and Operations
Function: Engineering
Experience Level: Not Applicable