Head of Global Assurance

Scale seeks a Head of Global Assurance to lead a high-performing team of technical experts advancing Scale’s assurance programs across its Global Public Sector and Commercial business units.

This is a leadership role for an experienced assurance cybersecurity compliance or GRC professional who can manage a team of senior technical experts drive execution across complex government and customer requirements and partner closely with Global Public Sector Enterprise Security Engineering Product and the Legal team.

• Lead assurance programs across Scale’s Global Public Sector and Commercial businesses including FedRAMP NIST frameworks SOC 2 ISO 27001 and other customer regulatory and business assurance requirements.
  
• Manage and develop a technical assurance team responsible for public sector authorizations commercial assurance audits customer commitments control evidence remediation and reporting.
  
• Set priorities and operating cadences for assurance workflows including intake evidence collection control owner follow-up remediation tracking metrics and deadline management.
  
• Build the metrics dashboards and reporting cadences that give company leadership a clear view of program health key risks and strategic priorities.
  
• Partner with Legal on contract-driven assurance obligations sensitive escalations external-facing responses and customer-facing representation issues.
  
• Work closely with Global Public Sector Enterprise Security Engineering Product and other control owners to validate evidence track remediation and support authorization and audit requirements.
  
• Collaborate across Legal and GRC on a unified controls framework for security and other regulatory requirements.
  
• Manage relationships with external auditors assessors and certification bodies.

• 10+ years of experience in cybersecurity compliance GRC public and commercial sector assurance IT audit cloud security or related roles.
  
• Active U.S. security clearance SCI eligible.
  
• Experience leading global or region-specific assurance programs through scalable control frameworks and cross-functional execution.
  
• Experience managing senior technical assurance cybersecurity compliance GRC audit or control evidence professionals.
  
• Experience managing distributed teams across time zones.
  
• Deep familiarity with FedRAMP continuous monitoring authorization packages and related NIST frameworks.
  
• Experience leading customer assurance control evidence remediation reporting and audit workflows.
  
• Experience overseeing SOC 2 ISO 27001 and other commercial assurance frameworks.
  
• Experience with external assessors authorizing officials government customers public sector partners commercial auditors or certification bodies.
  
• Experience working with legal teams on contract-driven assurance obligations and strong judgment on when to escalate legal contractual technical security customer-facing or privileged issues.
  
• Excellent communication skills including the ability to explain technical assurance issues clearly to legal business security and executive audiences.

• Experience developing compliance or assurance approaches for emerging technologies including GenAI AI/ML data platforms or cloud infrastructure.
  
• Experience advising leadership on assurance compliance and risk tradeoffs in fast-moving technical environments.
  
• Experience with defense federal civilian classified national security GovCloud or JAB authorization environments.
  
• Ability to translate new or ambiguous technical issues into practical compliance controls and implementation plans.

• Relevant certifications such as CISSP CISM CISA CCSP AWS Certified Solutions Architect Azure Solutions Architect or similar credentials.

What We Do

Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR image video and NLP annotation APIs allow machine learning teams at companies like OpenAI Lyft Pinterest and Airbnb focus on building differentiated models vs. labeling data.