AI Enterprise Security Engineer

Docusign-posted 9 days ago

Full-time • Mid Level

Hybrid • San Francisco, CA

5,001-10,000 employees

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We are seeking a talented and proactive AI Enterprise Security Engineer to join our team. In this role, you will be responsible for designing, implementing, and maintaining security solutions that enable the safe and responsible use of AI/ML tools and systems by employees across the organization. You will collaborate with engineering, product, and security teams to ensure that employee-facing AI initiatives are secure, compliant, and aligned with business objectives. This position is an individual contributor role reporting to the Sr Director of AI and Data Security.

Develop and execute enterprise-wide AI security strategies focused on the secure adoption and usage of AI/ML tools by employees
Design and implement security controls for employee-facing AI/ML platforms, applications, and supporting infrastructure
Collaborate with cross-functional teams to integrate security best practices into the AI/ML tool selection, deployment, and usage lifecycle
Conduct threat modeling, risk assessments, and security reviews for AI/ML systems and tools accessed or used by employees
Identify and mitigate AI/ML-specific vulnerabilities, such as adversarial attacks, model misuse, and unauthorized access in employee workflows
Establish and operationalize governance frameworks and guardrails for responsible AI tool adoption and usage across the organization
Develop and enforce policies for safe and compliant employee use of AI/ML, including user access controls, monitoring, and incident response
Ensure compliance with internal security standards, industry frameworks, and regulatory requirements related to employee use of AI/ML
Translate technical security risks into business impact and communicate recommendations to stakeholders and leadership
Define and track measurable security outcomes related to employee AI/ML usage, reporting progress to executive leadership
Mentor and support other engineers and employees in AI security best practices
Stay current with emerging AI security threats, tools, and research, and proactively update security measures for employee-facing AI/ML
Support customer-facing security teams in security assurance activities as needed

5+ years of experience in application or product security, with at least 1 year focused on AI/ML systems
Experience with AI/ML concepts, architectures, and frameworks
Experience with secure software development practices and tools
Experiece with common AI/ML security threats and mitigation techniques
Experience in programming languages such as Python, Java, or C++
Experience with cloud platforms (AWS, Azure, GCP) and securing cloud-based AI/ML deployments
Experience with ssecure software development practices, AI/ML model security, and data governance
Experience operationalizing security governance and compliance in complex environments
Demonstrated ability to translate technical security risks into business context and actionable recommendations

Excellent communication and collaboration skills
Bachelor’s or Master’s degree in Computer Science, Information Security, or a related field
Excellent stakeholder management and communication skills across technical and business audiences
Strong cross-functional collaboration and stakeholder management skills, especially with Product, Engineering, Data, Privacy, and executive teams
Experience with privacy-preserving machine learning techniques (e.g., differential privacy, federated learning)
Knowledge of relevant regulations and standards (e.g., GDPR, NIST, ISO 27001) as they pertain to employee data and AI/ML usage
Experience with MLOps, CI/CD pipelines, and enterprise-scale AI deployments
Experience with exploiting common security vulnerabilities
Knowledge of common exploit mitigations and how they work
Coding and scripting experience in one or more general purpose languages
Certifications: CAIP, CISM, CRISC, CISSP, CCSP, or equivalent
Familiarity with attack surface monitoring, supply chain security, and continuous control validation
Experience driving automation strategies, predictive analytics, and data-driven insights
Knowledge of frameworks such as NIST CSF, NIST AI RMF, ISO 27001, ISO 42001, FAIR, SOC 2, and FedRAMP

Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
Paid Time Off: earned time off, as well as paid company holidays based on region
Paid Parental Leave: take 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

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