Software Engineer - Apple Services Engineering

Job description

Apple Services Engineering (ASE) teams power the App Store, Apple TV+, Apple Music, Apple Podcasts, Apple Books, Fitness+, the iTunes Store, and more. We do this on a significant scale, delivering a huge variety of software in over 35 languages to more than 150 countries. Our engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services. Thanks to Apple's unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although Services are a bigger part of Apple's business than ever before, our teams remain small, nimble, and highly cross-functional, offering greater exposure to the array of opportunities here. Minimum Qualifications: 5+ years of professional software engineering experience, with demonstrated ability to own features throughout the software development lifecycle, from design and development through production support. Experience designing and developing scalable, highly observable, and resilient backend services and RESTful APIs. Strong proficiency in Java (and one or more backend programming languages such as Kotlin, Go, or Python). Solid understanding of distributed systems, concurrency, networking, and service-oriented architectures. Experience with databases, data modeling, and cloud-native application development. Experience with containerized applications, CI/CD pipelines, and modern software development practices. Hands-on experience building production applications powered by Large Language Models (LLMs), including integrating models into backend services and working with concepts such as prompting, retrieval, structured outputs, or tool/function calling. Strong analytical, communication, and collaboration skills. Ability to solve problems given incomplete or partial data and/or requirements. Driven to deliver high-quality solutions consistently and quickly. Bachelor’s degree in CS/CE/EE or a related technical field, or equivalent industry experience. Preferred Qualifications: Experience building large-scale distributed systems, data pipelines, or event-driven architectures. Familiarity with one or more of these technologies: NoSQL databases (Cassandra, DynamoDB), messaging systems (Kafka/RabbitMQ), Solr/Elasticsearch, Redis, SQL (PostgresSQL, MySQL), Spring Framework/Spring Boot, Docker, Kubernetes etc. Experience building advanced LLM applications using Retrieval-Augmented Generation (RAG), vector databases, semantic search, AI agents, and production-grade evaluation and guardrails. Experience integrating foundation models through platforms such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, AWS Bedrock, Hugging Face, or self-hosted open-source models. Experience evaluating AI systems using model evaluation frameworks, prompt testing, guardrails, observability, and performance benchmarking. Experience mentoring peers and influencing technical direction through collaboration, technical leadership, and knowledge sharing.