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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Staff AI Security Engineer - **Company:** ServiceNow - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $190,900.0 - $334,100.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Systems Engineering, Artificial Neural Networks, Biometrics, Cyber Security, Data Discovery, Data Governance, Data Structures, Distributed Systems, Intrusion Detection and Prevention, Python (Programming Language), Machine Learning, OAuth, Pattern Recognition, Performance Tuning, Tensorflow, Zero Trust Network Access, Big O, Azure Machine Learning, Data Streaming, Supervised Learning, Data Classification, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Information Technology, Real Time Data, Apache Kafka, Free and Open-Source Software, Malware Detection, Machine Learning Operations, Api Design, Stream Processing, Data Pipelines, Unsupervised Learning, Servicenow - **Published:** September 9, 2026 - **Apply:** https://jobs.smartrecruiters.com/ServiceNow/744000148359929-senior-staff-ai-security-engineer ## About the Role * 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. ## Description 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., * 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., We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. ## Related Videos - [The New AI Security Stack: Observe, Detect, Protect](https://www.wearedevelopers.com/videos/100302-the-new-ai-security-stack-observe-detect-protect) - [Keeping applications secure by evolving OAuth 2.0 and OpenID Connect](https://www.wearedevelopers.com/videos/100152-keeping-applications-secure-by-evolving-oauth-2-0-and-openid-connect) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Delay the AI Overlords: How OAuth and OpenFGA Can Keep Your AI Agents from Going Rogue](https://www.wearedevelopers.com/videos/1637-delay-the-ai-overlords-how-oauth-and-openfga-can-keep-your-ai-agents-from-going-rogue) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Trustworthy AI Starts at Deployment: 5 Checks Before You Ship](https://www.wearedevelopers.com/magazine/753-trustworthy-ai-starts-at-deployment-5-checks-before-you-ship)