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.\nProficiency in Node or Python and ability to read/write the other.\nExperience with RESTful/GraphQL APIs and automated testing frameworks (e.g., Playwright, Jest, Selenium, XCUITest).\nExperience 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).\nShipped 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).
8+ years as a Software Engineer and 5+ years in automation or platform tooling.\nRetrieval + RAG expertise (e.g., Pinecone, Qdrant, OpenSearch; re-ranking, hallucination evals, chunking strategies).\nStrong Python for ML/LLM workflows; advanced TypeScript and Node for platform services.\nPlatform integration of AI agents, quality policies, and data-driven dashboards.\nStrong fundamentals in mocking, dependency injection, and distributed systems.\nExperience 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).\nExperience with cross-platform automation frameworks across web, native, and APIs; and reducing flakiness and improving time-to-signal via heuristics/stats.\nExperience 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.\nExperience creating deterministic test data: seeding known records, masked subsets, synthetic data; managing golden dataset versioning and lineage.\nAbility to explain complex systems simply to engineers and non-engineers.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 7736f6d0e057e5706d3a00d0837cefe
- Posted 10 hours ago
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