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RMF/Security Risk Assessor

Dark Wolf SolutionsWorldwide | | Remote, Hybrid, Onsite
This job is no longer open

Dark Wolf Solutions


is seeking an experienced RMF Security Risk Assessor with expertise in the Risk Management Framework (RMF) to join our team. The successful candidate will have strong technical abilities, including coding skills and a comprehensive understanding of security risks in cloud environments. As a Security Risk Assessor, you will provide Security Assessment and RMF expertise to help our client streamline processes, improve systems, and enhance product delivery and lifecycle management. This role is essential in providing significant impacts to the program, helping teams navigate the cATO and deployment processes efficiently while maintaining high standards of security and compliance.

Key responsibilities may include but are not limited to:

  • Overseeing the continuous Authorization to Operate (cATO) assessment process for multiple applications.
  • Ensuring applications going into production minimize risk and comply with client and program policies and requirements.
  • Assessing and mitigating risks associated with the deployment and operation of applications in cloud environments.
  • Collaborating with cross-functional teams to manage the lifecycle of various capabilities, from configuration to enhancement and development.
  • Overseeing data management processes to ensure data integrity and security.
  • Providing support for ongoing operations and maintenance of systems to ensure security and compliance.
  • Applying HCD methodologies to the design and development of products, ensuring user-centric solutions.

Required Qualifications:


  • 7+ years of relevant experience in providing RMF expertise
  • Experience in cATO and Fast Track ATO processes and procedures
  • A Certified Kubernetes Administrator (CKA) certification is highly desirable to understand risks in cloud environments
  • Previous experience in security risk assessment and management, especially in cloud-based systems
  • Ability to meticulously assess security risks and ensure compliance with client and program requirements
  • Strong verbal and written communication skills to effectively collaborate with cross-functional teams and stakeholders
  • Proactive approach to identifying and mitigating risks in systems and processes
  • Bachelor’s in Statistics, Mathematics, Computer Science or another related field
  • US Citizenship and ability to obtain a Secret security clearance 

Desired Qualifications:


  • Strong coding experience 

This position will be a remote/hybrid role based out of multiple hubs including: Herndon, VA, Colorado Springs, CO, Atlanta, GA and Omaha, NE. The salary range for this position is estimated to be between $160,000.00 - $180,000.00, commensurate on experience and technical skillset.We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

This job is no longer open

Life at Dark Wolf Solutions

Dark Wolf Solutions provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. By combining the most innovative emerging technologies with deep federal domain expertise, Dark Wolf operates at the nexus of technical innovation and mission needs.
Thrive Here & What We Value1. EEO/AA Employer2. Minorities/Women/Veterans/Disabled and other protected categories3. Continuous Learning and Improvement Mindset4. Hybrid Work Environment Supported5. Strong Technical Skills and Analytic Ability Valued6. Excellent Communication and Collaboration Skills Emphasized7. Attention to Detail and Organizational Abilities Expected8. Continuous Monitoring Practices Familiarity Preferred
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