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In office (Austin)
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Middle · 3+ years exp
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Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Nov 11, 2026. Apple scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

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.

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