Senior/Staff/Principal AI/ML Engineer

Job Description: AppGate is seeking a Senior/Staff/Principal AI/ML Engineer to design, build, and operationalize detection algorithms, ML inference pipelines, and risk aggregation systems for its autonomous Agentic AI threat detection platform. The role sits at the intersection of identity security, behavioral analytics, and applied machine learning, building systems that analyze ZTNA logs in near real-time. The engineer will surface high-fidelity threat signals feeding into the Risk Sentinel enforcement engine to continuously harden access decisions. Job Responsibilities: -Build advanced detections to identify threats early, including identity compromise, privilege escalation, impossible travel, and data exfiltration across identity, network, device, and session telemetry -Design and develop accurate and explainable risk scoring systems that normalize and correlate detection signals into dynamic user, device, and session risk scores that drive adaptive access enforcement decisions -Build scalable, low-latency streaming pipelines that process ZTNA events in near real time, enabling resilient, high-throughput security analytics -Define and implement security controls for autonomous AI agents, including detection of agent drift, unauthorized resource access, prompt injection attacks, privilege escalation, data leakage, and other emerging threats in Agentic AI systems -Leverage agentic AI to automate threat investigation, contextual analysis, and remediation workflows for high-confidence security incidents (roadmap) -Train, evaluate, and deploy ML models on real-world identity and network telemetry, tuning for production precision and recall targets Job Requirements: -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 -Hands-on experience designing detections for identity-based threats such as credential compromise, privilege escalation, insider activity, behavioral anomalies, and data exfiltration -Experience building and operating scalable MLOps platforms 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 -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 -Real-time or near-real-time pipeline experience with Kafka, Flink, Spark Streaming, or equivalent, and familiarity with lakehouse formats such as Apache Iceberg and Parquet -Security domain knowledge of MITRE ATT&CK, identity threat kill chains, ZTNA or network access control systems, and audit log analysis -Mission-driven, production-focused, signal-obsessed mindset with a focus on measuring precision and recall and eliminating alert fatigue Salary: $180,000 - $300,000 /year To Apply: https://apply.workable.com/appgate/j/53EA1923CA/