DevOps Engineer, Info Apps

The Info Apps DevOps team provides the infrastructure backbone for Apple News, Stocks, Weather, and Apple Creator Studio, powering experiences used by millions of users worldwide and fueling capabilities like Siri AI's World Knowledge Answers. This team owns CI/CD pipelines, infrastructure automation, developer tooling, and operational support for large-scale backend systems deployed across hybrid cloud environments. Join us to shape how software is built, deployed, and scaled across some of Apple's most beloved consumer products.

Description

In this role, you will design and build infrastructure that serves millions of concurrent users across multi-cloud and on-premises environments, with a primary focus on development tooling, deployment automation, and CI/CD pipeline improvements. You will partner closely with engineering and SRE teams to architect scalable solutions using Kubernetes, AWS, and GitOps workflows. Day-to-day work is roughly 70% automation and tooling development and 30% operational support, giving you deep hands-on ownership across the full software delivery lifecycle.

Minimum Qualifications

3+ years of experience in a DevOps or infrastructure-focused engineering role, including work on systems at large scale (millions of concurrent users) Expert-level proficiency with Kubernetes and container orchestration, including deployment, lifecycle management, and troubleshooting on EKS or equivalent managed Kubernetes platforms Advanced scripting skills in Python, Bash, Groovy or Java , applied to automation workflows and custom tool development Deep expertise in CI/CD systems including ArgoCD, Jenkins, and Gradle/Maven, paired with advanced Git and GitOps workflow experience Proven experience managing cloud platforms (AWS and/or GCP), covering compute, networking, storage, and managed services Hands-on experience with Infrastructure as Code tools such as Terraform, Pulumi, or CloudFormation to manage resources and build reusable abstractions Solid understanding of Linux operating systems, shell scripting, and core networking concepts including TCP/IP, DNS, HTTP, and load balancing Demonstrated ability to debug complex distributed systems and solve ambiguous infrastructure problems under production conditions

Preferred Qualifications

Familiarity with Generative AI concepts and experience supporting AI/ML development environments, model operationalization, or platforms such as SageMaker Experience maintaining and debugging Spring-based Java runtime environments in a DevOps or platform engineering context Strong background in modern web services architectures including REST APIs, microservices, and service mesh patterns Proficiency with data infrastructure components such as Cassandra, Kafka, Solr, Postgres, or Redis in a large-scale backend environment Track record of working closely with product engineering and SRE teams to define and enforce deployment standards across multi-team organizations