Principal Platform Engineer People Systems

At Apple we believe the people who build our products deserve systems built with that same care. That belief is what drives People Systems. Behind every revolutionary hardware launch breakthrough service and magical customer experience are the passionate people who make it all is our pursuit: to be the unseen force behind a world-class employee experience for the most exceptional people on Earth realized through obsessively crafting and caring for the systems that hire reward and support our talent as they grow thrive and do the best work of their at the vibrant intersection of technology people and business we architect the platforms behind every stage of that journey: Recruiting Onboarding Core HR Payroll Compensation and Benefits. Our systems dont just process transactions; they shape how people experience working here.

When you engineer for People Systems your users are Apples most vital asset: its People. We are seeking a visionary Application Architect to shape the technical strategy for People Systems with a passion for platforms where configuration is the product and agentic workflows that redefine whats will be working on a Platform that helps define features. Data models rules workflows permissions screens and reports are all versioned configuration interpreted at runtime so the people closest to a problem can change how the system behaves without waiting for a release. Hundreds of components must behave as one system. We are looking for an Application Architect who can make that value engineers who bring both technical excellence and product thinking. Youll make the architectural calls that balance fast delivery against long-term platform health and build systems that are scalable secure and resilient by design rather than by retrofit. This role requires someone who thrives on complexity but ships is central to how we work. Youll partner with product managers and cross-functional engineering teams to understand problems deeply before reaching for solutions. The best engineers here are the ones who ask why before how. If you care deeply about precision data integrity and crafting platforms where scale meets human empathy come join us to do the best work of your life.

Architect applications configuration-first: decide what belongs in versioned configuration versus code keep both on one coherent model and feed platform gaps back to the platform teams as concrete requirementsnMove fluently between components of very different character from compiled kernels where correctness is absolute to search UI and AI services where scale latency and non-determinism dominate and choose the patterns and guarantees that fit eachnSet the core application patterns: one canonical document model saga-based orchestration and a hard line between recorded facts and the decisions made about themnGuarantee data integrity consistency and privacy in high-stakes domains where decisions affect peoples careers enforced where data is read and written so that unsafe access is inexpressible rather than left to caller disciplinenOwn end-to-end system design for new business initiatives starting with a systems impact analysis across the existing platform ecosystemnDesign APIs with strong contracts and clear versioning so dozens of consuming teams can build confidently without coordination overheadnLead the design and coding of modular domain-driven services on Java / Kotlin Spring Boot and cloud-native infrastructure and the event streams that carry complex high-concurrency workloads; set the testing strategy and hold the bar in code reviewnBring an AI-native SDLC and agent orchestration to platform engineering: shape how agents are specified composed evaluated sandboxed and promoted both in how we build the platform and where agents act inside applications with tool interfaces over platform APIs validated structured output and deterministic fallbacksnDefine and uphold reliability: SLOs observability incident response and zero-downtime deployments; diagnose the hardest distributed-systems failures and tune high-volume batch and real-time pipelinesnEstablish architecture standards reference designs and platform blueprints for teams to adopt and be the go-to technical authority guiding partner teams as they design against and integrate with our platformsnBring clarity to ambiguous problems and drive decisions that balance innovation scalability reliability and compliance; present technical strategy modernization options capacity risk and technical-debt retirement to leadershipnMentor and elevate engineers across teams so the organisations technical capacity grows beyond any one persons contributionnAutomation Development: Design and build tools to streamline database management tasks and performance tuning. Integrate AI/ML capabilities into areas like intelligent configuration recommendations workload-aware scheduling and LLM-powered interfaces that simplify complex operator workflowsnAPI-Driven Services: Design build and maintain secure versioned microservices that expose database lifecycle operations as APIs. Ensure correctness under concurrent execution handle partial failures gracefully and evolve the API surface to support new capabilities without breaking existing consumersnContinuous Integration/Continuous Deployment (CI/CD): Integrate database management automation into CI/CD pipelines with automated testing canary rollouts and rollback capabilitiesnMonitoring and Alerting: Develop and enhance monitoring alerting and health-check systems that give both the platform team and customers deep visibility into database health. Build self-healing mechanisms that detect and remediate known failure patterns automatically

15 years of professional software engineering in system design technical architecture or solution architecture for large-scale enterprise solutions; BS/MS in Computer Science Software Engineering or a related field or equivalent practical experiencenLed the architecture of a configuration-driven platform used by multiple engineering teams: metadata models multi-tenancy extensibility versioned APIs and safe publish promote and rollback of configurationnProficient across technology stacks rather than tied to one: has built components of very different character in one system (interpreters or compilers of declarative input query and authorization layers workflow and state engines search and reporting UI runtimes) picking up whatever language framework or datastore each demands with the judgement to apply the right guarantees to eachnDistributed-systems depth: consistency models fault tolerance partitioning and failure-mode analysis; designed for high availability and horizontal scale under variable load serving millions of users and high-volume transactionsnStrong foundation in event-driven and event-sourced architecture: saga and workflow orchestration streaming platforms change data capture and transactional data storesnEvolved schemas and contracts at scale: backward-compatible change of metadata and configuration models breaking-change detection and migration of in-flight data and workflowsnDeep proficiency in Spring Boot (or equivalent) and microservices patterns with async fluency: virtual threads (Java 21) coroutines or reactive programmingnExpert use of relational or NoSQL databases at scale: schema design query optimization migrations and transaction managementnHands-on experience with an AI-native SDLC and agent orchestration frameworks: working with coding agents under tests and review and building with tool calling graph-based orchestration context management and structured-output validationnCloud-native production experience on AWS or comparable platforms (Kubernetes identity and access management cost governance) operating with monitoring alerting incident response and a post-mortem culturenSet technical direction across multiple teams without direct authority: break down ambiguous problems without detailed specs translate business requirements into designs and explain trade-offs clearly to engineers and executives

Built expression languages rule engines or policy engines (typed ASTs multiple execution backends) and the differential and conformance testing that keeps those backends consistentnExperience decomposing or extending monolithic enterprise systems into service-based platforms that interoperate with the existing system of record while the business ran uninterruptednBackground in CQRS event sourcing or saga-based orchestration for long-running workflowsnFamiliarity with compliance and audit requirements for sensitive personal data (PII regulated HR data) and AI governance: drift detection bias monitoring explainability and audit trailsnExperience putting LLMs and ML into production backend services: inference APIs RAG pipelines vector search embeddings evaluation and observability tooling prompt and context engineeringnProven record of leading technical decisions cross-functionally aligning non-engineering stakeholders on trade-offs and moving engineering culture toward measurable reliability correctness cost ownership and evaluation-driven developmentnDesigned APIs consumed by many teams (versioning contract stability documentation) and integrated with enterprise platforms through APIs ETL or event streams amid many upstream and downstream dependenciesnDeveloper experience for platform consumers: SDKs local test harnesses simulation environments and self-service onboardingnFluency with AI-assisted development tools and AI-augmented operations such as predictive alerting automated root-cause analysis and self-healing runbooksnDesigned evaluation guardrail and human-in-the-loop strategies for AI systems that make or inform consequential decisionsnHands-on chaos engineering and advanced reliability practice: failure injection game days capacity modeling and traffic shaping