AI & Data Security Engineer

Imagine what you could do here. At Apple new ideas have a way of becoming outstanding products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could Sales organization generates the revenue needed to fuel our ongoing development of products and services. This in turn enriches the lives of hundreds of millions of people around the world. We are in many ways the face of Apple to our largest US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting implementing and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.

Were looking for an AI u0026 Data Security Engineer responsible for securing data across the full AI lifecycle from data classification and enforcement of access controls to model deployment and agentic applications. This role designs and enforces row-level security policies API-driven access controls and role-based data grants across AI pipelines chat interfaces and autonomous agents. Partners closely with Data Governance Legal and Engineering to align AI data usage with enterprise policy and regulatory requirements. Leads red team exercises to proactively identify vulnerabilities in AI systems and drives remedial actions. Owns the development of security standards and guidelines that enable product teams to build AI applications securely by default at scale.

Design and implement security architecture for AI use cases ensuring secure data access and usage through role-based access controls and authorized AI use cases are aligned with Apples data classification standards including appropriate data handling storage retention requirements and access and manage user id and persona based row-level security policies for data stored in Snowflake and other data systems connected to US and maintain row-level security policies based on user identity and persona across DBX and other data platforms supporting U.S. and implement API-based security controls for AI applications including authentication authorization and data access policies to protect sensitive information and ensure compliant data adversarial testing of AI systems to identify vulnerabilities drive remediation and safeguard Apple data from misuse and malicious and enforce data access boundaries for AI agents governing permitted data sources actions and restricting sensitive data and enforce data access policies for LLM-powered chat applications governing usage of structured and unstructured data sources documents and context that may be surfaced in agentic with Data Governance Legal Privacy and Engineering teams to ensure AI data usage complies with enterprise policies regulatory requirements (e.g. GDPR CCPA) and internal data governance u0026 Audit AI data access pipelines through logging anomaly detection and audit trails to detect unauthorized access data exfiltration attempts or policy and enforce US-wide AI data security standards best practices and developer guidelines to implement role-based access controls enabling secure-by-default data practices at scale.

8 years of professional experience in data security cybersecurity security architecture or data engineering with a primary focus on Platform Security: Proven hands-on experience designing and implementing Role-Based Access Control (RBAC) row-level and column-level security policies in modern cloud data platforms (specifically Snowflake and/or Databricks/DBX).nAPI u0026 Application Security: Strong expertise in API security controls authentication and authorization protocols (e.g. OAuth2 OIDC SAML JWT) to protect data Skills: Proficiency in Python Java Go or similar languages used for scripting automation and building security controls within data u0026 Privacy: Solid understanding of data privacy regulations (e.g. GDPR CCPA) and experience translating these regulatory requirements into technical data governance and access u0026 Auditing: Experience implementing security logging audit trails and monitoring solutions to detect unauthorized access or data : Bachelors degree in Computer Science Cybersecurity Information Systems or equivalent practical experience.

AI/ML Security Expertise: Direct experience securing AI/ML lifecycles LLM-powered applications or autonomous AI agents (e.g. securing RAG architectures mitigating prompt injection defining data access boundaries for AI).nAdversarial Testing: Experience leading or participating in red team exercises penetration testing or threat modeling specifically tailored to machine learning models and AI -Functional Leadership: Demonstrated ability to partner effectively with non-technical stakeholders including Legal Privacy and Data Governance teams to establish and enforce enterprise wide security Threat Detection: Experience building or deploying anomaly detection systems to identify malicious activity within complex data Skills: Strong technical writing skills with a track record of creating developer guidelines security standards and best practices that enable secure-by-default engineering at u0026 Certifications: Masters degree in a relevant field or industry recognized security certifications (e.g. CISSP CISM Cloud Security certifications).