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Manager Cyber Risk Management (Threat Detection & Automation Engineering)
Delta Dental Ins. · Flexible / Remote
Publicada em 06/08/2026
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*This role does not offer visa sponsorship. Candidates must be authorized to work in the U.S. without current or future sponsorship (including CPT, OPT, TN or H-1B). The Manager of Cyber Risk Management owns the definition, execution, and continuous evolution of enterprise security threat management technology capabilities. This role is critical to advancing Delta Dental's cyber defense capabilities into a future state defined by automation, AI augmentation, and rapid, effective response. The manager will lead the engineering team responsible for the platforms, data, analytics, and automation capabilities that protect the organization by ensuring cyber threats are identified and neutralized before business impact occurs. This role is responsible for defining and executing the technology roadmap that enables scalable, resilient, and effective threat detection and response capabilities.This leader pursues measurable security outcomes across people, processes, and technology. The role collaborates closely with the Security Operations and Incident Response teams, delivering high-quality services and capabilities that support threat detection and response efforts.This individual will lead a multidisciplinary team responsible for detection engineering, platform implementation and administration (e.g., SIEM, EDR, NDR, IPS), and agentic and deterministic automation and orchestration.Responsibilities:Own and execute the cyber threat management engineering strategy, driving transformation toward highly automated, AI-augmented cyber operations.Translate strategic objectives into actionable roadmaps, aligning team priorities with enterprise cyber risk management goals.Drive measurable improvements in operational effectiveness and reduction of risk impact.Ensure platform resilience, scalability, and alignment with evolving attack surfaces (cloud, SaaS, AI-driven environments).Champion the continued adoption of AI, machine learning, and automation to enable autonomous investigati
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