Cloud Security Engineer

Position Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate business processes and simplify people’s lives. Using Docusign’s Intelligent Agreement Management platform, companies create, commit, and manage agreements with industry‐leading e-signature and contract lifecycle management solutions. As a Cloud Security Engineer focused on AI security, you will shape how we safely adopt AI by ensuring vendor-provided AI and ML solutions are thoroughly tested, hardened, and deployed securely. In this individual contributor role reporting to the Director, Platform Security, you’ll work closely with engineering and data science teams to probe for vulnerabilities, validate data handling, and build robust controls for third-party AI technologies.

Key Responsibilities

• Inspect and validate how vendor AI/ML models handle sensitive data during ingestion and inference, including testing for data leakage, memorization, encryption, and tenant isolation
• Design and implement secure integration patterns for AI solutions in the cloud, such as API gateways and sandboxing, and partner with the red team to assess and strengthen input/output flows
• Build and maintain monitoring hooks and guardrails to detect model misuse, drift, anomalous output, or potential data exfiltration
• Implement technical safeguards and automation, including filtering layers, rate-limiting, DLP for prompts/responses, and synthetic data pipelines to minimize sensitive data exposure
• Collaborate with engineering, data science, and security teams to embed security into AI development and deployment workflows
• Partner with platform engineers and security architects to develop secure deployment patterns and reusable reference architectures
• Conduct threat modeling for AI/ML-specific attack surfaces (e.g., model inversion, membership inference, data poisoning, adversarial examples) and drive mitigations
• Support incident response and remediation for security events involving AI systems
• Document security processes, runbooks, and best practices for AI in the cloud
• Stay current with emerging threats and best practices in AI and cloud security

Required Qualifications

• 2+ years of experience in cloud security engineering, application security, or a related field
• Bachelor’s or Master’s degree in Computer Science, Information Security, or a related technical field (or equivalent experience)
• Experience with penetration testing, application security, or offensive security, including applied knowledge of AI/ML attack vectors
• Experience in testing APIs, cloud SaaS integrations, and vendor platforms for vulnerabilities
• Experience with AI/ML pipelines and associated risks (e.g., model training vs. inference, adversarial examples, data leakage)
• Experience implementing technical controls for data protection, access management, and monitoring in cloud or high-risk systems
• Experience with scripting or programming languages (e.g., Python, Go, or similar) for automation and testing
• Experience collaborating with engineering, data science, and security teams

Preferred Qualifications

• Experience securing AI/ML workloads or platforms in cloud environments (e.g., Azure AI, AWS SageMaker, Google AI Platform)
• Experience with regulatory compliance frameworks relevant to AI and cloud (e.g., GDPR, HIPAA, SOC 2)
• Experience with cloud security posture management (CSPM), CNAPP, or related solutions (e.g., Wiz, Microsoft Defender)
• Experience with threat modeling and risk assessment for AI/ML systems
• Experience with data privacy, secrets management, or PKI in cloud-based AI solutions

Benefits & Perks

• Salary: Washington, Maryland, New Jersey and New York (including NYC metro area): $109,600.00 - $156,950.00 base salary
• Schedule: Hybrid (Minimum 2 days per week in-office)
• Paid Time Off: Earned time off, as well as paid company holidays based on region
• Paid Parental Leave: Up to six months off with your child after birth, adoption, or foster care placement
• Full Health Benefits Plans: Options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: Select retirement and pension programs with potential for employer contributions
• Learning and Development: Options for coaching, online courses, and education reimbursements
• Compassionate Care Leave: Paid time off following the loss of a loved one and other life-changing events