Senior Staff AI Security Engineer
AI summary of the role
Senior Staff AI Security Engineer on the Platform Security Core team, architecting enterprise-scale AI security systems that integrate ML, inference engines, and real-time reasoning into identity, access control, threat detection, and data governance.
What you’ll do
- Design and implement ML-driven security systems for identity risk, anomalous access, malware classification, and sensitive data discovery.
- Build high-performance inference pipelines and contextual reasoning systems for real-time distributed security decisions.
- Integrate AI into access control and identity with adaptive authentication, behavioral biometrics, and confidence scoring.
- Lead complex technical initiatives combining ML research, systems engineering, and security domain expertise.
What you’ll bring
- 10+ years software development with Bachelor's, 8+ with Master's, 6+ with PhD, or equivalent.
- Hands-on implementation of ML algorithms from scratch, not just using libraries.
- Deep programming expertise in Java and/or Python with systems-level knowledge.
- Proven track record deploying ML systems in production at significant scale.
Technologies
Java · Python · TensorFlow · PyTorch · Kafka · RAG · LLM · OAuth · mTLS · feature stores
About ServiceNow
Enterprise AI workflow platform connecting people, systems, data, and agents so large organizations can automate IT, employee, customer, security, and industry operations.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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
More from the job description
Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people. Job Description 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 wil [... source excerpt omitted ...] pertise. 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 app [... source excerpt omitted ...] rogramming 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, tuni
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