Software Engineer (Quality), Retail and Marcom Engineering

Marcom is the creatively-led global team that oversees Apples 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 Platformshared services APIs and evaluation pipelines that improve CI/CD signal quality for engineering QE and production teams. Youll 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 youll prototype quickly tie engineering to business outcomes and balance rigor with AI-driven velocity. Youll build and extend the quality platformorchestration retrieval evaluation harnesses and APIsthat scales quality across the portfolio.

Build platform services that normalize data from PRs specs logs and test runs and surface signals in a central dashboardnEvolve 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 signalnCodify guardrails by implementing thresholds and Pass or Warn or Block verdicts with lightweight change historynPrototype quickly and deliver end to end from design to launch with fast disciplined iterationsnPartner across Engineering to drive adoption and a simple developer experiencenShip agentic workflows to automate test generation defect triage and CI/CD gatesnIntegrate LLM and retrieval to power internal QE copilots and PRs or Slack embeds

Requires Bachelors degree in Computer Science a technical field or a minimum of 5 years of relevant work in Node or Python and ability to read/write the 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 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 integration of AI agents quality policies and data-driven fundamentals in mocking dependency injection and distributed 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/ building and integratingREST and federated GraphQL (e.g. Apollo Federation v2)services including subgraph/endpoint development schema/API composition and deployment collaboration with platform creating deterministic test data: seeding known records masked subsets synthetic data; managing golden dataset versioning and to explain complex systems simply to engineers and non-engineers.