Senior Software Engineer, Apple Services Engineering
This role involves building and maintaining large-scale distributed data processing systems and AI-driven workflows to support Apple's media services like Apple TV+. Engineers will work with big data technologies and LLM integration to create scalable, privacy-focused infrastructure.
- Compensation
- Not disclosed
- Location
- Cupertino
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Computer Engineering, or a related field.
- 5+ years of experience developing and maintaining production-grade applications using Java and/or Scala.
- 5+ years of experience designing and building large-scale distributed systems using technologies such as Apache Spark, Apache Flink, Apache Kafka, or Cassandra.
- Hands-on experience working with Artificial Intelligence (AI) technologies, including building MCP Servers, designing Agentic workflows, and integrating Large Language Models (LLMs).
Nice to have
- Good understanding of software engineering principles and fundamentals including algorithms and data structures.
- Self-directed, self-motivated and ability to create architecture and design documents.
- Ability to assemble multi-functional requirements and translate them into practical engineering tasks.
Full description
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you can accomplish. Would you like the stimulation and challenges of building elite, extraordinary scalable systems that power App Store, Apple Music, Apple TV+, Apple Fitness+, Apple Arcade and many more? Then this is the opportunity for you at Apple! We strive to provide a flawless experience for millions of customers and developers. We are seeking a Software Engineer to join Apple Services Engineering (ASE) who brings deep passion for building distributed large scale data processing systems, frameworks and platforms using big data technologies. You will partner with Apple TV and Video teams and work collaboratively to make a significant impact on Apple TV customers.
At Apple, data is our first-class citizen and we build the systems that make it extraordinary.
We operate at petabyte scale, engineering distributed platforms that power real-time insights, fuel business decisions, and directly shape the experiences behind Apple TV and Sports products. Our work sits at the intersection of massive-scale data infrastructure and cutting-edge AI, and no two days look the same.
One day, you're architecting real-time streaming pipelines with Apache Flink, processing millions of events per second with sub-second latency. The next, you're building intelligent AI Agentic workflows and MCP servers that unlock new dimensions of automation and decision-making. And on another, you're designing LangGraph-powered workflows that bring the full potential of Large Language Models into production-grade data systems.
Our systems must scale effortlessly, remain highly available, and deliver consistent, trustworthy results, because the collaborators and stakeholders who depend on our data use it to drive critical business requirements. The stakes are high, and the impact is real.
Above all, we are deeply committed to Apple's privacy principles, not as a constraint, but as a core value that guides every architectural decision we make.
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, or a related field.
- 5+ years of experience developing and maintaining production-grade applications using Java and/or Scala.
- 5+ years of experience designing and building large-scale distributed systems using technologies such as Apache Spark, Apache Flink, Apache Kafka, or Cassandra.
- Hands-on experience working with Artificial Intelligence (AI) technologies, including building MCP Servers, designing Agentic workflows, and integrating Large Language Models (LLMs).