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 there's no telling what you could accomplish.

Apple's 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 customers.

Apple's 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.

Description

We're looking for an AI & 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.

Minimum Qualifications

8+ years of professional experience in data security, cybersecurity, security architecture, or data engineering with a primary focus on security.

Data 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).

API & Application Security: Strong expertise in API security controls, authentication, and authorization protocols (e.g., OAuth2, OIDC, SAML, JWT) to protect data access.

Programming Skills: Proficiency in Python, Java, Go, or similar languages used for scripting, automation, and building security controls within data pipelines.

Compliance & Privacy: Solid understanding of data privacy regulations (e.g., GDPR, CCPA) and experience translating these regulatory requirements into technical data governance and access controls.

Monitoring & Auditing: Experience implementing security logging, audit trails, and monitoring solutions to detect unauthorized access or data exfiltration.

Education: Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or equivalent practical experience.

Preferred Qualifications

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).

Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems.

Cross-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 standards.

Advanced Threat Detection: Experience building or deploying anomaly detection systems to identify malicious activity within complex data pipelines.

Communication 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 scale.

Education & Certifications: Master's degree in a relevant field, or industry recognized security certifications (e.g., CISSP, CISM, Cloud Security certifications).