Cybervance

Cybervance

Cloud Incident Response Training- Contract Instructors

Kensington, MD · Contract

Sponsorship not specifiedDetected 190 days ago
PowerShellAzureCybersecurityMicrosoft SentinelMicrosoft DefenderKQLSOARIncident Response

About the role

  • These courses span foundational, intermediate, and advanced levels, with a focus on Microsoft Azure tools, methodologies, and practical applications for incident response and forensics.

Responsibilities

  • Deliver live virtual training that explores the differences between cloud and on-premises incident response, ensuring participants understand the Shared Responsibility Model and its implications for security investigations.
  • Support proactive defense strategies by teaching Azure-specific playbook creation, threat modeling, and leveraging cloud-native tools for artifact collection, automation, and advanced detection.

Nice to have

  • Relevant certifications (e.g., Azure Security Engineer, Azure Administrator, CISSP, GCFA, GCIH).
  • Familiarity with conducting forensic analysis of virtual machines, containers, and serverless functions in Azure.
  • Experience designing and delivering incident response playbooks and cloud automation workflows
  • Experience designing and delivering incident response playbooks and cloud automation workflows Cybervance is an equal opportunity employer.
  • Proven expertise in cloud incident response, with a focus on Microsoft Azure security tools and frameworks.
  • Prior experience teaching technical content to security professionals, preferably in virtual environments.
  • In-depth understanding of Azure architecture, logging sources, PowerShell, Microsoft Defender Suite, Sentinel, and SOAR.
  • Knowledge of threat hunting, advanced log analysis, and cloud-specific attack patterns.

Skills

  • Kensington, MD Remote | 1099

Benefits

  • Create an engaging and interactive learning environment, answering participant questions and ensuring key objectives are met.

This listing is sourced directly from Cybervance's careers page and normalized into a canonical job model.