Network Detection & Response Engineer - Remote

Role: Security Platform / NDR EngineerLocation: RemoteContract - C2C/W2/1099Duration: 6 months to 1 yearOverviewWe are seeking a skilled engineer to support and enhance our Network Detection & Response (NDR) platform, ensuring high availability, strong observability, and effective security operations. The role combines security operations expertise with automation and modern monitoring engineering.Key ResponsibilitiesSupport daily operations of the NDR platform, including sensor health, data flow monitoring, and alert management.Design and implement a platform health monitoring solution using Grafana, Prometheus, and InfluxDB.Develop Python-based automation for collecting, processing, and exposing system and application health metrics via APIs.Build and maintain dashboards and alerting systems for real-time visibility into platform performance and uptime.Collaborate with Security Operations, Incident Response, and Network Engineering teams to ensure timely detection and resolution of issues.Required QualificationsExperience with network security and NDR tools such as Corelight, Zeek, Suricata, or Endace.Strong Python programming skills, particularly for automation and API integration.Hands-on experience with observability tools: Grafana, Prometheus, and/or InfluxDB.Solid understanding of networking fundamentals (TCP/IP, traffic flow, packet capture).Experience in SOC, NDR monitoring, or security operations environments.Familiarity with building dashboards, alerts, and custom data collection pipelines.Exposure to containerized environments (Docker, Kubernetes).Knowledge of API authentication and data integration best practices.Preferred SkillsExperience in building scalable observability or security monitoring platforms.Understanding of large-scale network telemetry systems.AI Enablement RequirementRegular use of enterprise-approved AI tools (e.g., GitHub Copilot, Microsoft 365 Copilot, GenAI platforms).Application of AI for coding, documentation, analysis, and workflow optimization.Commitment to continuous learning and adoption of evolving AI capabilities.