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 portfolioBuild platform services that normalize data from PRs, specs, logs, and test runs and surface signals in a central dashboard Evolve the execution layer by operating shared runners with fair queues and hardened images and by adding observability and repeatable test data to reduce infra flakiness and speed time to signal Codify guardrails by implementing thresholds and Pass or Warn or Block verdicts with lightweight change history Prototype quickly and deliver end to end from design to launch with fast, disciplined iterations Partner across Engineering to drive adoption and a simple developer experience Ship agentic workflows to automate test generation, defect triage, and CI/CD gates Integrate LLM and retrieval to power internal QE copilots and PRs or Slack embedsRequires Bachelors 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.