Software Engineer (Quality), Retail and Marcom Engineering

Apple•Sunnyvale, CA

11d

About The Position

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. DESCRIPTION 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.

Requirements

Requires Bachelor’s degree in Computer Science, a technical field or a minimum of 5 years of relevant work experience.
Proficiency in Node or Python and ability to read/write the other.
Experience with RESTful/GraphQL APIs and automated testing frameworks (e.g., Playwright, Jest, Selenium, XCUITest).
Experience either improving reliability of shared CI/test infrastructure (e.g., lower infra flakiness, faster queue/start times) or operating a CI runner fleet (agents/executors; GitHub Actions, Jenkins, or Harness).
Shipped one LLM-powered feature (e.g., RAG over internal docs/telemetry; triage agent; stability investigator; natural-language to automation; eval harnesses; CI gates for accuracy/latency).

Nice To Haves

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 and federated GraphQL (e.g., Apollo Federation v2) 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.