Software Engineer (Platform Software Engineer), G&A Solutions Engineering (GSE)

Summary

G&A Solutions Engineering (GSE) is IS&T's dedicated technology partner for Apple's general and administrative functions — including people, finance, facilities, legal, and security. The team builds and delivers integrated technology solutions that keep these functions running efficiently and securely at global scale. GSE also works closely with business teams to develop custom tools that improve productivity and bring greater automation and consistency to G&A operations across Apple.

Description

When you engineer for People Systems, your users are Apple’s most vital asset: its People. We are seeking a Senior Platform Engineer to shape the technical strategy for People Systems with a passion for platforms where configuration is the product, and agentic workflows that redefine what's possible.

You 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 a passionate engineer who can make that true.

We value engineers who bring both technical excellence and product thinking. You'll 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 simplicity.

Collaboration is central to how we work. You’ll 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.

Responsibilities

• Design, build and own components of a configuration-driven platform, from design to production, hands-on, growing from well-scoped components to whole services
• Make configuration safe to change: validated, versioned and previewable before release, with controlled promotion across environments and rollback
• Build security, tenancy and privacy into the platform itself, so that unsafe access is impossible rather than left to caller discipline
• Build event-driven services that handle high-concurrency, multi-tenant workloads reliably
• Design APIs and contracts with clear versioning and compatibility checks, so consuming teams can build without coordination overhead
• Help interdependent components behave as one system, respecting boundaries and contracts, and fixing issues that span components
• Own correctness: write the tests that prove it, build quality gates into the delivery pipeline so every change, whether written by a person or an agent, is verified before it ships, and take part in code review
• Diagnose and fix distributed-systems issues through to a root-cause fix
• Operate what you ship: build observability in, deploy without downtime, and take a share of on-call
• Work AI-natively: build with coding agents in an orchestrated workflow and verify their output with tests and review
• Automation 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 workflows
• API-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 consumers
• Continuous Integration/Continuous Deployment (CI/CD): Integrate database management automation into CI/CD pipelines with automated testing, canary rollouts, and rollback capabilities
• Monitoring 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
• Build agents for the AI SDLC that generate, run, triage and maintain tests, and the automation and quality gates around them
• Contribute designs and reference implementations, and partner with architects and product to turn ambiguous problems into clear specs

Minimum Qualifications

• 4 years of professional backend or platform engineering, building scalable distributed systems
• 4 years experience in building or contributing to components of a configuration-driven or metadata-driven platform used by multiple teams: metadata models, multi-tenancy, extensibility and versioned APIs
• 4 years of professional development in TypeScript or Java (21+) and Spring Boot (or equivalent), microservices patterns and async programming: virtual threads, coroutines or reactive programming
• 4 years of working knowledge of distributed systems: consistency, fault tolerance, partitioning and failure-mode analysis
• BS/MS in Computer Science, Computer Engineering, or a related field, or equivalent practical experience

Preferred Qualifications

• Comfortable across technology stacks rather than tied to one: picks up whatever language, framework or datastore a component demands
• Experience with event-driven systems on Kafka (or equivalent): ordering, idempotent consumers, replay and schema evolution
• Working expertise with relational or NoSQL databases: schema design, query optimization, migrations and transaction management
• Designed or contributed to APIs and contracts consumed by other teams: versioning, backward compatibility and documentation
• Experience with multi-tenant or security-sensitive systems: authorization, data isolation and audit
• Operated production systems: monitoring, alerting, health checks, incident response and a post-mortem culture, with working knowledge of rollout practice (canary, feature flags, rollback)
• Demonstrated experience with AI-native development in an orchestrated workflow: specifying tasks for coding agents, coordinating them across steps, and verifying their output with tests and review
• Test engineering and delivery automation fundamentals: test design and the test pyramid, deterministic and contract tests, flaky-test management, and CI/CD pipelines
• Ability to break down ambiguous problems with guidance and to communicate trade-offs clearly to engineers and product partners
• Experience running configuration-driven systems where non-engineers change behaviour, including validation, impact preview, promotion and rollback
• Background in CQRS, event sourcing, or saga-based orchestration patterns for long-running workflows
• Experience building platform-based solutions in the People space
• Familiarity with compliance and audit requirements in systems handling sensitive personal data (PII, financial, or regulated HR data)
• Experience decomposing or extending monolithic systems into services that interoperate with an existing system of record
• Fluency with developer experience for platform consumers: SDKs, local test harnesses and self-service onboarding
• Experience building agents that act on engineering workflows (test generation, code review, failure triage), with sandboxed execution and human approval for any change
• Experience building self-healing automation that detects and remediates known failure patterns, with safe limits and human approval for risky actions