Apple's Marcom Platform & Services Quality Engineering team is seeking a full-stack Software Engineer to enhance internal tools into a quality platform, leveraging AI/ML to improve automated testing, reduce flakiness, and accelerate CI signal for high-visibility product launches.
Requirements
- Proficiency in Node or Python and ability to read/write the other.
- Built and owned an automation framework (e.g., Selenium, Jest, Playwright) or test infrastructure for at least one platform (web, native, or APIs).
- Shipped an internal or external LLM-powered capability (e.g., prompting with tool/function calls, automated evals, or CI gating; understands accuracy/latency/cost trade-offs).
- Designed and operated REST/GraphQL services and data flows that feed automation/test systems; solid integration-testing practice.
- Experience in CI/CD (e.g., GitHub Actions/Jenkins/Harness) and Docker.
- Cross-platform automation frameworks across web, native, and APIs; experience reducing flake and improving time-to-signal via heuristics/stats.
- Retrieval/RAG depth: metadata filtering, chunking, index design, re-ranking, evaluation; familiarity with vector databases (e.g., Qdrant, Pinecone, OpenSearch) and embeddings.
Responsibilities
- Build LLM-assisted quality capabilities that generate test plans/cases from specs and code changes, implement self-healing tests, detect flaky tests, and perform change-impact analysis.
- Design a retrieval layer (embeddings + vector search) over specifications, PRs, logs, and historical test artifacts to power internal QA copilots and developer experiences.
- Own how we test using AI-create test sets, set CI gates, alert on regressions-and report accuracy, coverage gains, hallucinations, latency, and cost.
- Design and develop platform APIs for use in automation frameworks.
Other
- Requires Bachelor’s degree in Computer Science, a technical field or a minimum of 5 years of relevant work experience.
- 8+ years as a Software Engineer and 5+ years in automation & validation.
- Strong Python for ML/LLM workflows; advanced TypeScript and Node for platform services.
- Kubernetes and infrastructure-as-code exposure.
- Expertise in mocking / dependency injection.
