Senior/Staff/Principal AI/ML Engineer - Agentic AI Security

About AppGate

AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution. AppGate is the only direct-routed ZTNA solution built for peak performance, superior protection and seamless interoperability. AppGate safeguards Fortune 500 enterprises worldwide. Learn more at appgate.com. 

About the Role

We're looking for a senior AI/ML Engineer who will design, build, and operationalize the detection algorithms, ML inference pipelines, and risk aggregation systems that power our autonomous Agentic AI threat detection platform.

You'll work at the intersection of frontier AI, agentic systems, and Zero Trust security, exploring emerging AI architectures and building production-grade systems that detect sophisticated threats, understand complex security behaviors, and enable intelligent security automation.

Responsibilities

•       Threat Detection Engine: Build advanced detections to identify threats early, including identity compromise, privilege escalation, impossible travel, and data exfiltration across identity, network, device, and session telemetry.

•       Agentic AI Systems: Design and develop multi-agent AI workflows that automate complex security engineering tasks, including threat research, detection development, evaluation, and optimization.

•       AI-Native Threat Detection: Develop innovative threat detection approaches using small language models (SLMs), foundation models, and emerging AI architectures to identify complex attack patterns and behavioral anomalies.

•       Model Training & Optimization: Fine-tune, evaluate, and optimize AI models for security-specific tasks, balancing detection accuracy, inference latency, throughput, and computational efficiency.

•       High-Performance AI Inference: Design and build scalable, low-latency model serving infrastructure capable of supporting near-real-time security analytics and decision-making.

•       Autonomous Remediation (Roadmap): Leverage agentic AI to automate threat investigation, contextual analysis, and remediation workflows, enabling intelligent containment and response for high-confidence security incidents.

•       Train, evaluate, and deploy ML models on real-world identity and network telemetry; tune for production precision and recall targets.

Required Qualifications

•        5+ years of production AI/ML engineering experience, with a strong preference for candidates who have built threat detection, UEBA, ITDR, or identity security platforms at leading security or cloud companies.

•        Generative AI & Foundation Models: Strong understanding of modern AI architectures, including LLMs, SLMs, Transformers, fine-tuning, embeddings, and efficient inference techniques.

•        Agentic AI Development: Experience building AI agents or multi-agent workflows using LLM orchestration frameworks, tool calling, retrieval-augmented generation (RAG), or similar approaches.

•        MLOps & Productionization: Experience building and operating scalable MLOps platforms for AI/ML systems, including model lifecycle management, CI/CD for ML pipelines, feature stores, automated retraining, model monitoring/drift detection, experiment tracking, and deployment orchestration using Kubernetes, MLflow, Kubeflow, SageMaker, or equivalent tooling in high-throughput production environments.

•        ML proficiency: Experience building AI-powered security systems using large language models, deep learning, and agentic AI techniques for threat detection, anomaly analysis, contextual investigation, and intelligent remediation.

•        Data & streaming engineering: Real-time or near-real-time pipeline experience (Kafka, Flink, Spark Streaming, or equivalent); familiarity with lakehouse formats (Apache Iceberg, Parquet).

•        Security domain knowledge: MITRE ATT&CK, identity threat kill chains, ZTNA or network access control systems, and audit log analysis.

•        Mindset: Mission-driven, production-focused, signal-obsessed. You measure precision and recall, you eliminate alert fatigue, and you care that your work protects real systems.

This is your chance to build the AI systems that detect, prevent, and auto-remediate threats across networks, users, and autonomous AI agents.

If you are an experienced AI/ML Engineer who has built identity or network threat detection platforms at scale and wants your next platform to protect the people and infrastructure the world depends on — we want to hear from you.

AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.  Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities.  In furtherance of AppGate’s policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company’s EEO Coordinator. www.appgate.com/careers