Software Engineer (Quality), Retail and Marcom Engineering

Marcom is the creatively-led global team that oversees Apple’s consumer facing marketing.

We ensure the flawless development and execution of world-class communications across all medias and platforms.The Marcom Quality Engineering team is hiring a full-stack Software Engineer to help turn internal tooling into a Quality Platform—shared services, APIs, and evaluation pipelines that improve CI/CD signal quality for engineering, QE, and production teams.

You’ll apply modern AI/ML to expand automated coverage,reduce infrastructure and test flakiness, and accelerate time-to-signal. This work supports high-visibility launches for millions of customers across 100+ languages.

As a Software Engineer, you’ll prototype quickly, tie engineering to business outcomes, and balance rigor with AI-driven velocity. You’ll build and extend the quality platform—orchestration, retrieval, evaluation harnesses, and APIs—that scales quality across the portfolio

Requires Bachelor's degree in Computer Science, a technical field or a minimum of 5 years of relevant work experience in the US. Programming fundamentals demonstrated across multiple projects or large/shared codebases, with the ability to ramp quickly as the stack evolves, including designing asynchronous, event-driven systems — applying concurrency, non-blocking I/O, and sound failure handling at scale.

Experience with RESTful/GraphQL APIs and automated testing frameworks. Experience either improving liability of shared CI/test infrastructure or operating a CI runner fleet. Shipped one LLM-powered feature.

8+ years as a Software Engineer and 5+ years in automation or platform tooling. Retrieval + RAG expertise (e.g., Pinecone, Qdrant, OpenSearch; re-ranking, hallucination evals,chunking strategies). Strong Python for ML/LLM workflows; advanced TypeScript and Node for platform services.

Platform integration of AI agents, quality policies, and data-driven dashboards. Strong fundamentals in mocking, dependency injection, and distributed systems. Experience building shared execution images/runners and multi-tenancy controls (hardened, versioned images; isolation/quotas; fair queuing) on a company internal cloud (e.g., Kubernetes or an internal scheduler).

Experience with cross-platform automation frameworks across web, native, and APIs; and reducing flakiness and improving time-to-signal via heuristics/stats. Experience building and integrating REST services, including subgraph/endpoint development, schema/API composition, and deployment collaboration with platform teams.

Experience creating deterministic test data: seeding known records, masked subsets, synthetic data; managing golden dataset versioning and lineage. Ability to explain complex systems simply to engineers and non-engineers.