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.
Responsibilities
Build 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 embeds
Requirements
8+ years as a Software Engineer and 5+ years in automation or platform tooling.
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.
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).
Pay & Benefits
Note: Apple benefit, compensation and employee stock programs are subject to
Additional Information
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.
Apple · Sunnyvale, CA