Software Engineer – Digital Asset Management, Retail & Marcom Engineering

Responsibilities

You will design and develop next-generation enterprise asset platforms that manage, transform, and distribute massive volumes of creative assets. The role involves integrating machine learning and generative AI capabilities into foundational workflows to support mission-critical systems.

Requirements

Candidates must have a bachelor's degree in a technical field and at least 3 years of professional software engineering experience with a focus on backend systems. Strong proficiency in Java and experience with distributed systems, databases, and API design are required.

Skills

• Java
• Spring Boot
• RESTful APIs
• Apache Kafka
• PostgreSQL
• Elasticsearch
• OpenSearch
• Milvus
• Pinecone
• Machine Learning
• Generative AI
• Distributed Systems
• Cloud Computing
• Docker
• Kubernetes
• OpenTelemetry

About this role

At Apple, we strive every single day to craft products and platforms that enrich
people’s lives. Our successes are the result of skilled domain experts working
in an environment that encourages creativity, collaboration, and rethinking old
problems in new ways. Retail and Marcom Engineering, an IS&T team, builds and
operates the systems and experiences that connect Apple's products with its
customers. The team owns the technology behind both Apple's online and physical
stores and drives the interactive marketing experiences and tools that keep
creative operations moving. Together, those functions deliver the technology
behind every product story Apple tells and every purchase a customer makes.

DESCRIPTION

As a member of the Digital Asset Management (DAM) Engineering team, you will
design and develop next-generation enterprise asset platforms that manage,
transform, index, and distribute massive volumes of creative and digital assets
worldwide. You will sit at the intersection of enterprise software engineering,
machine learning, and generative AI—infusing intelligent search, semantic
understanding, auto-tagging, multimodal indexing, and AI-driven automation into
foundational asset workflows. You will have the unique and rewarding opportunity
to shape high-scale, mission-critical systems relied upon daily by
cross-functional teams across Apple. Our team is looking for a passionate,
technically skilled software engineer who thrives in designing scalable
distributed backend systems and integrating cutting-edge machine learning and
generative AI capabilities. You will work autonomously within a collaborative
team, partnering closely with product managers, ML practitioners, platform
architects, and downstream engineering teams. We rely on your technical
leadership and hands-on expertise to design resilient architectures, evolve
enterprise DAM platforms, and implement robust AI/ML pipelines that deliver high
impact.

MINIMUM QUALIFICATIONS

Bachelor’s degree in Computer Science, Computer Engineering, or related
technical field, or equivalent practical experience. 3+ years of professional
software engineering experience with a strong focus on backend systems. Strong
proficiency in Java (including modern Java features, concurrency, performance
profiling, and frameworks such as Spring Boot). Practical experience designing
and operating RESTful APIs, event-driven architectures, or distributed streaming
systems (e.g., Apache Kafka or equivalent modern message brokers). Familiarity
with database technologies (relational databases such as PostgreSQL and
search/vector stores like Elasticsearch, OpenSearch, or Milvus/Pinecone).

PREFERRED QUALIFICATIONS

Digital Asset Management Experience: Hands-on experience developing,
configuring, or extending enterprise or open-source DAM platforms or similar
content repository engines. Understanding of core computer science concepts,
including algorithms, data structures, distributed systems, and concurrent
programming. Experience with cloud platforms (e.g., AWS, GCP, Alibaba Cloud). ML
& Generative AI Integration: Hands-on experience applying ML or generative AI in
production software, such as integrating machine learning inference services,
large language models, embeddings, vector databases, computer vision models, or
LLM-based pipelines (e.g., LangChain, model serving via Triton/TorchServe,
prompt engineering, or multimodal search). Distributed Storage & Media
Processing: Familiarity with cloud object storage (S3), content delivery
networks (CDNs), and media processing pipelines. DevOps & Cloud-Native Tooling:
Working familiarity with Docker, Kubernetes, infrastructure-as- code, and
production telemetry (OpenTelemetry, Prometheus, Grafana). Strong analytical
problem-solving skills, with enthusiasm to tackle ambiguous technical challenges
in a fast-paced environment.

About Apple

Computers and Electronics Manufacturing · 10,001+ employees · headquartered in Cupertino, California · founded 1976