Full Stack AI Systems Engineer

Imagine what you could do here. At Apple we believe new insights have a way of becoming excellent products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could people here at Apple dont just build products they build the kind of wonder thats revolutionized entire industries. Its the diversity of those people and their ideas that inspires the innovation that runs through everything we do from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found Systems and Infrastructure (MSI) team is an engineering organization under the Product Operations org. MSI is responsible for the design development and maintenance of systems tools services and applications required to efficiently run manufacturing operations at scale across global factory sites.

As a Full Stack AI systems Engineer on the MSI team you will design build and evolve web applications and services that empower Manufacturing Operations. You will work closely with engineers to understand their workflows and challenges translate those needs into effective technical solutions and take features from early concept through production. Your work will span the user experience backend services APIs data flows and AI capabilities that power these care deeply about the user experience and think in systems: how components fit together where the right abstractions belong and how todays decisions shape tomorrows roadmap. You will apply AI thoughtfully as part of the overall product experience and use modern development tools including LLM-powered tools to improve delivery while maintaining a high bar for quality reliability and architecture. Because this work involves close collaboration with our users and partners the ideal candidate combines strong engineering judgment with curiosity communication and ownership.

Own features and applications from problem definition and technical design through implementation deployment adoption and continuous and build production-quality full stack applications including user interfaces backend services APIs data models and AI-powered and agentic capabilities that connect with engineering data and tools to support multi-step workflows and application architecture and maintain high standards for scalability reliability security testing observability and user across teams incorporate user feedback and contribute reusable tools patterns and technical guidance.

Bachelors degree in Computer Science or a related field or equivalent practical experience.n3 years of experience delivering production software through the full software development lifecycle from requirements and system design to implementation testing deployment and ongoing foundation in software engineering principles including architecture API and data design testing debugging security reliability performance and building full stack applications and the ability to work effectively across user interfaces backend services integrations and data using modern development tools including AI-assisted coding tools while applying sound engineering judgment to review validate and improve generated with cloud platforms (AWS Azure or GCP) Kubernetes Docker CI/CD and Infrastructure as ability to understand complex user workflows translate them into practical technical solutions and collaborate across teams to deliver measurable communication and collaboration skills with the ability to translate technical concepts into clear business focused insights.

Bachelors or Masters degree in Computer Science or a related field or equivalent practical delivering production software through the full software development lifecycle from requirements and system design to implementation testing deployment and ongoing genuine passion for systems architecture thinking and a habit of reasoning about how components data and services fit together at scalenExperience using AI coding tools such as Claude Code or Continue to enhance the development workflow and accelerate delivery while maintaining code quality and architectural standardsnExperience integrating LLMs or ML services into production applications for example prompt design retrieval augmented generation agentic workflows or model backed featuresnFamiliarity with message and job queues such as RabbitMQ Kafka and with distributed systemsnExperience with cloud platforms and containerization tools such as Docker and KubernetesnStrong understanding of UX and UI design principles.