Job description

In this high-impact role, you will bridge the gap between traditional security practices and emerging AI risks. Operating under Zero Trust principles and Secure by Default framework, you will partner with engineering, data science, product, and compliance teams to build "paved roads" — pre-approved, reusable, secure-by-default patterns that enable teams to build AI-driven systems without a bespoke review for every project. you will amplify the effectiveness of the entire security function, by reducing inbound request volume through proactive foundational work and providing developers, ML engineers, and traditional security architects with clear guidance and standardized controls, Leveraging deep AI/ML knowledge, you will evaluate risks such as data poisoning, model manipulation, and prompt injection, while simultaneously applying AI to security workflows to automate threat modeling, design reviews, and control validation. The third dimension of this role beyond prevention and response, is scale: applying AI-driven tooling to extend the team's reach far beyond what headcount alone can achieve. This is a highly strategic and technical role that bridges AI innovation with security, enabling Apple to adopt AI confidently and at pace. As part of the Advisory Arm, you will also contribute directly to the Self-Service Enablement Platform, codifying decisions, patterns, and trade-offs from your reviews into AI-powered guidance accessible to teams without direct advisory engagement. Additionally, by working on Apple's most cutting-edge AI projects, you will serve as an intelligence sensor for the broader ARC team: identifying emerging AI/ML technologies and architectural patterns that should become future foundational focus areas, ensuring the organization stays ahead of the threat landscape. BS in Computer Science, Computer Engineering, or Information Security, or 6+ years of equivalent, hands-on security experience in large enterprise environments a plus. Strong background in security architecture, application security, or cloud security Demonstrated understanding of AI/ML concepts, pipelines, and risks (e.g., data poisoning, prompt injection, model inversion, model theft) Experience with threat modeling methodologies (e.g., STRIDE) and secure design principles Familiarity with AI regulatory frameworks such as the EU AI Act, NIST AI RMF, ISO/IEC 42001, or comparable standards Ability to communicate security concepts clearly to both technical and non-technical stakeholders Proven ability to partner with engineering, data science, and product teams to drive adoption of security requirements Experience applying AI/LLMs for security automation (e.g., risk analysis, automated threat modeling, compliance validation) Proficiency in at least one scripting or programming language (e.g., Python, Swift, Java) Experience performing full-stack security architecture reviews encompassing cloud-native and emerging AI/ML technologies Experience designing security patterns for LLM-based systems, RAG pipelines, or agentic architectures Familiarity with Zero Trust architecture principles and Secure by Default design Experience with data protection, encryption architecture, and key management in AI/ML contexts Strong verbal and written communication skills, with the ability to build consensus across diverse teams A real passion for staying ahead of emerging AI security risks and translating that knowledge into actionable guidance Deeply accountable for your work; upbeat, adaptable, and results-oriented

Requirements

Must-haves

Strong background in security architecture, application security, or cloud security
Demonstrated understanding of AI/ML concepts, pipelines, and risks (e.g., data poisoning, prompt injection, model inversion, model theft)
Experience with threat modeling methodologies (e.g., STRIDE) and secure design principles
Familiarity with AI regulatory frameworks such as the EU AI Act, NIST AI RMF, ISO/IEC 42001, or comparable standards
Ability to communicate security concepts clearly to both technical and non-technical stakeholders
Proven ability to partner with engineering, data science, and product teams to drive adoption of security requirements
Experience applying AI/LLMs for security automation (e.g., risk analysis, automated threat modeling, compliance validation)
Proficiency in at least one scripting or programming language (e.g., Python, Swift, Java)
Experience performing full-stack security architecture reviews encompassing cloud-native and emerging AI/ML technologies
Experience designing security patterns for LLM-based systems, RAG pipelines, or agentic architectures
Familiarity with Zero Trust architecture principles and Secure by Default design
Experience with data protection, encryption architecture, and key management in AI/ML contexts
Strong verbal and written communication skills, with the ability to build consensus across diverse teams
A real passion for staying ahead of emerging AI security risks and translating that knowledge into actionable guidance
Deeply accountable for your work; upbeat, adaptable, and results-oriented

Nice-to-haves

BS in Computer Science, Computer Engineering, or Information Security, or 6+ years of equivalent, hands-on security experience in large enterprise environments a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythonswiftjavallm

Platform: apple
Effort: medium