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.

 

To be successful in this role you have:

Core Experience

• Bachelor's degree with 10+ years of software development experience; OR Master's degree with 8+ years; OR PhD with 6+ years; OR equivalent work experience.
• Hands-on experience implementing machine learning algorithms from scratch—not just using libraries, but understanding how models work at a fundamental level.
• Deep programming expertise in Java and/or Python, including systems-level knowledge and performance optimization.
• Proven track record building and deploying machine learning systems in production environments at significant scale.
• Strong fundamentals in computer science: algorithms, data structures, complexity analysis, system design, and distributed systems.

AI/ML Systems Expertise

• Deep understanding of machine learning fundamentals: supervised learning, unsupervised learning, model evaluation, feature engineering, and model selection.
• Hands-on experience with neural networks, deep learning frameworks (TensorFlow, PyTorch), and modern model architectures.
• Experience training, tuning, and deploying models: hyperparameter optimization, regularization, preventing overfitting, and achieving production-grade model quality.
• Understanding of model inference: latency optimization, quantization, model serving infrastructure, and real-time prediction pipelines.
• Experience with LLMs and large-scale foundation models: fine-tuning, retrieval-augmented generation (RAG), prompt engineering at scale, and understanding of model weights and token economies.
• Knowledge of reasoning and agentic systems: how to apply contextual analysis, multi-step reasoning, and decision logic on top of models.
• Experience with feature engineering, feature stores, and ML data pipelines at scale.
• Familiarity with model observability and monitoring: detecting model drift, performance degradation, and retraining strategies.

Security Architecture Expertise

• Deep knowledge of identity and access control systems: how authentication, authorization, and access decisions flow through enterprise systems.
• Experience applying machine learning to security problems: anomaly detection, attack classification, risk scoring, and threat pattern recognition.
• Understanding of sensitive data landscapes: PII detection, data classification frameworks, and data governance strategies.
• Familiarity with security operations: how detection systems, alert triage, and incident response workflows operate at scale.
• Knowledge of common attack patterns and threat models relevant to enterprise security.
• Experience integrating security solutions with platform infrastructure: API design, event streaming, and decision-making in critical paths.

Nice to Have

• Experience with Kafka, stream processing, or real-time data systems for security applications.
• Hands-on work with cryptography, zero-trust architectures, or OAuth/mTLS.
• Experience deploying models in regulated environments with compliance and governance requirements.
• Track record mentoring junior engineers and driving technical excellence across teams.
• Open-source contributions to ML or security projects.

 

For positions in this location, we offer a base pay of $190,900 - $334,100, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.