Software Engineer - Digital Asset Management

Apple

About The Position

Content Solutions Engineering, part of Apple’s IS&T organization, builds and maintains the Content Management systems — including Digital Asset Management (DAM) — that empower Apple’s business teams to author, manage, and publish content across a wide range of channels. We build the systems that sit behind every piece of content Apple’s customers and employees interact with, at scale and with high reliability. We’re looking for a backend engineer who is passionate about building resilient, high-throughput systems that make it effortless for content teams to manage, discover, and deliver digital assets across Apple’s ecosystem. You will design, build, and operate backend services for our Digital Asset Management platform, working closely with content, publishing, and platform engineering teams to deliver reliable, scalable systems that power content authoring and delivery across Apple’s public and internal properties.

Requirements

3+ years of software engineering experience, with a focus on backend or distributed systems.
Programming skills in Java, with hands-on experience building services using Spring Boot.
Experience building or operating Digital Asset Management systems, content management systems, or media processing/transcoding pipelines.
Experience working on metadata and search layer: schema modeling, controlled vocabularies, faceted query APIs, and metadata extraction from embedded sources.
Experience building rendition and derivative generation services — thumbnails, previews, web-optimized variants — orchestrated asynchronously at scale.
Experience designing and building REST APIs for high-throughput, production-grade systems.
Experience with NoSQL data stores such as MongoDB and/or DynamoDB, including schema/data modeling for scale.
Experience with Kafka or similar event-streaming/messaging systems.
Experience with search technologies such as Solr or Elasticsearch.
Experience deploying and operating services in containerized, cloud environments (AWS, EKS/Kubernetes).
Strong collaboration and communication skills, with the ability to work effectively across cross-functional teams.
BS/MS in Computer Science, Software Engineering, or equivalent practical experience.

Nice To Haves

Experience with metadata and taxonomy design for large-scale content or asset repositories.
Hands-on experience or interest in AI/agentic tooling — such as AI-driven metadata tagging, agentic workflows, LLM-powered automation, or building MCP (Model Context Protocol) servers — applied to real engineering use cases.
Experience with CDN configuration and storage optimization for content delivery at scale.
Proficiency with Git and collaborative software development workflows.
Experience mentoring engineers and leading projects or technical design discussions.

Responsibilities

Design and build scalable backend services and APIs for asset ingestion, transcoding, metadata management, and taxonomy services using Java and Spring Boot.
Build and operate high-throughput ingestion and transcoding pipelines that process a wide variety of digital asset types at scale.
Design and implement search and retrieval APIs for digital assets, leveraging Solr/Elasticsearch for fast, relevant asset discovery.
Develop and maintain rights and licensing enforcement mechanisms to ensure assets are used and distributed in compliance with content policies.
Integrate DAM services with upstream and downstream content workflows, enabling seamless authoring-to-publish experiences across channels.
Work with data stores such as MongoDB and DynamoDB to design efficient, scalable data models for asset metadata and taxonomy.
Use Kafka to build event-driven, resilient pipelines connecting ingestion, processing, and downstream consumption of assets.
Deploy and operate services on AWS, using EKS for container orchestration in a large-scale, highly available environment.
Optimize storage and CDN usage to ensure fast, cost-effective delivery of digital assets across Apple’s global audience.
Explore and apply AI-driven and agentic approaches — such as AI-assisted metadata tagging, agentic workflows, and MCP (Model Context Protocol) servers — to improve content operations and reduce manual toil.
Collaborate closely with cross-functional engineering, content, and product teams, communicating clearly and effectively to align on requirements and trade-offs.
Mentor junior engineers and contribute to technical design discussions, fostering a culture of ownership, collaboration, and continuous learning within the team.