AIOps Software Engineer - Strategic Data Solutions

Summary

Do you want to join a team that is critical to the success of Apple? Join the SWE AIOps team and help us to make SDS operations excellent, supporting massive RT decision systems, large scale platforms, thousands of services/jobs on the back of petabytes of data.

We shape the next generation of customer data solutions by working on cutting-edge technologies and collaborating with talented teams across Apple. Our systems enable Apple engineering and operations teams to build the next ground breaking product. You'll be joining our diverse and talented team to summarize, simplify, and solve complex problems in our global ecosystem.

We advance technology by relying on each other's strengths and skills to build something bigger than ourselves. For this reason, team culture is central to our values. We value social skills and integrity as much as technical craft.

We are looking for extraordinary engineer with experience building large-scale data platforms, analytic tools and solutions to unlock AI Ops to scale for all of SDS. Do you excel in a high-demand setting and exceed expectations, in an environment that requires time-management? The right person will prioritize tasks and complete assignments ahead of schedule. While being a great standout colleague, you will also work independently.

Description

As a member of a multi-functional team, you'll have the opportunity to solve challenging software engineering and operational problems across a broad range of SDS services

• Provide Support for both Analytics and Realtime Platforms
• Develop applications to answer complex analytical and real-time operational questions
• Working with external teams to drive the development of infrastructure needs
• Help design, architect, build and maintain the applications and systems while using a variety of • Cloud and AI technologies
• Drive operational excellence across business-critical platforms through continuous exploration, benchmarking, and implementation of resilient operations and systems engineering solutions.
• Recognize opportunities for automation and tools improvements
• Provide hardware architectural guidance, estimate cluster capacity, and create roadmap
• Technical leadership with a focus on increasing operational maturity and skills across the team
• You will also be working closely with MLEs, other teams in SDS and also with business partners across Apple
• Adjust communication content and style to meet the needs of diverse stakeholders
• Ensures that different experiences, styles, backgrounds, and perspectives are leveraged appropriately.

Minimum Qualifications

BS or MS in Computer Science preferred; equivalent work experience considered

8+ years of work experience in Java, Scala, Python or equivalent programming language

8+ years of work experience in software engineering, data engineering or system engineering involving full development lifecycle

Fundamental grasp of computer science basics including data structures and algorithms

Hands-on experience with design and development in the Big Data and NoSQL technologies (such as Iceberg, S3, Cassandra, or Elastic Search)

Proven expertise in building and accelerating software development workflows using AI coding assistants and LLMs like Claude

Experience with application deployments using Docker and Kubernetes

Confirmed understanding of design and development of large scale, high throughput and low latency applications

Experience in handling architectural and design considerations such as performance, scalability, reusability and flexibility issues

Establishing standards, operational excellence, and delivery practices that other teams across SDS can adopt

Diagnose and resolve complex technical and operational issues escalated by the support and dev team

Ability to solve problems in collaboration with business partners

Proven technical leadership and communication skills

Possess strong aptitude and ability to learn new technologies quickly

Preferred Qualifications

Experience in developing batch and streaming Spark applications

Understanding of best practices and deploying pipelines in Cloud technologies like AWS

Leveraging AI-driven Application Performance Monitoring tools for predictive failure detection and automated root-cause analysis

Experience with large scale real time decisioning

Apply others’ diverse experiences, styles, backgrounds, and perspectives to get results

Contribute to a work climate where differences are valued and supported