SRE Manager - Data Infrastructure at Apple

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

13 May, 26

Salary

0.0

Posted On

12 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Kubernetes, Cloud Object Storage, Data Analysis, Automation, Collaboration, Infrastructure as a Service (IaaS), Python, Go, Rust, Amazon S3, Google Cloud Storage (GCS), Networking, Linux Internals, Distributed Systems, Configuration Management, Helm

Industry

Computers and Electronics Manufacturing

Description

At Apple, we don’t just build products — we create transformative experiences that have reshaped entire industries. Our innovation is driven by the diversity of our people and their ideas, inspiring everything we do. Imagine the impact you could make. Join Apple and help us leave the world better than we found it. The Data Virtualization Infrastructure (DVI) team is responsible for managing Apple’s largest multi-cloud storage abstraction and caching platform, which supports critical machine learning training workloads that power user-facing features across the Apple ecosystem. Operating across both first-party and third-party cloud environments brings complex and unique challenges. The SRE DVI team address these challenges through a strong foundation in cloud object storage, data analysis, automation, collaboration, and advanced expertise in Kubernetes. Our team oversees the full infrastructure stack — from low-level nodes to the complete network architecture — ensuring our platform remains highly available, resilient, and eﬃcient at scale. DESCRIPTION We are seeking an experienced Software and Systems Engineer to join our dynamic team as a technical manager. This role demands a proactive mindset, technical excellence, and a collaborative spirit. The ideal candidate will demonstrate experience of: Building and hiring a team of engineers in their respective timezones Strong critical thinking and a high degree of individual accountability Eﬀective communication and collaboration skills A genuine passion for Infrastructure as a Service (IaaS) A commitment to automation and operational eﬃciency Ownership of projects from design through delivery A solutions-oriented approach, coupled with the ability to gain alignment on technical direction Consistent and timely execution of design implementations aligned with project objectives The ability to provide constructive technical feedback, fostering team-wide growth and continuous improvement MINIMUM QUALIFICATIONS 7+ years experience in building, operating and scaling a large application in a private, public or hybrid cloud environment Experience hiring and leading a team of engineers in their respective timezones Deep expertise in Kubernetes, with hands-on experience using platforms such as Google Kubernetes Engine (GKE) or Amazon Elastic Kubernetes Service (EKS) Proficient in designing, developing, and releasing code in languages such as Python, Go, or Rust Practical experience with object storage technologies, including Amazon S3 or Google Cloud Storage (GCS) Strong background in designing and troubleshooting complex networking issues in both public and private cloud infrastructures Solid understanding of Linux internals, standard networking protocols, and distributed systems architecture PREFERRED QUALIFICATIONS Proven drive to automate manual operations and enhance processes through continuous iteration Strong understanding of best practices for deploying large-scale, distributed applications Hands-on experience managing diverse system environments using configuration management tools or software delivery platforms such as Spinnaker, Helm, or Flux Demonstrated expertise in deploying, supporting, and monitoring both new and existing services, platforms, and application stacks Solid familiarity with container orchestration and management using Kubernetes

Responsibilities

This role involves technical management of a team responsible for Apple’s large-scale multi-cloud storage abstraction and caching platform supporting machine learning workloads. The manager will oversee the full infrastructure stack, ensuring high availability, resilience, and efficiency across cloud environments.