Job Description
Apple Pay builds and operates the systems that power Apple Pay transactions at global scale, where downtime or a scalability shortfall means a failed payment for a real person at a register or checkout. This Architect role is responsible for setting the technical direction for how Apple Pay's systems achieve reliability, scalability, and availability — not just in design docs, but in the metrics, SLOs, and operational practices that hold them accountable in production. It is a role for someone with strong, well-reasoned opinions about how distributed systems should behave under load, failure, and partial degradation, and who can translate those opinions into concrete architecture, tooling, and team practices across the org.
The Architect will own the technical direction for Apple Pay's distributed systems — driving reliability engineering practices, observability strategy, and scalability architecture across a high-throughput, payment-critical infrastructure. Day to day, this means reviewing designs for resilience gaps, writing code and prototypes to validate architectural decisions, and leading incident reviews and postmortems that drive systemic fixes. The role also involves close collaboration with client, server, devops, and product engineering teams to ensure architecture decisions account for real-world operational constraints at Apple's global scale.
Preferred Qualifications
Experience with multi-region or globally distributed systems, including failover and disaster recovery design at scale
Prior experience in payments, fraud/risk systems, or other regulated, high-availability financial infrastructure
Contributions to open-source distributed systems projects or published technical writing on the subject
Experience establishing or maturing a devops/reliability practice within an organization
Minimum Qualifications
Proven track record designing and operating distributed systems at scale in high-throughput, low-latency production environments
Deep expertise in distributed systems fundamentals: replication, partitioning/sharding, consensus protocols, eventual vs. strong consistency, idempotency, and failure handling across network partitions
Hands-on experience defining and instrumenting metrics for availability and scalability (e.g., SLOs, error budgets, distributed tracing) and using them to drive concrete engineering decisions
Strong background in the building blocks of scalable systems: load balancing, caching layers, message queues/event streaming, database sharding/replication, service mesh, and rate limiting/backpressure mechanisms
Demonstrated ability to set technical direction across multiple teams without direct management authority, and to communicate trade-offs clearly to both engineers and leadership
Track record of leading incident reviews or reliability programs and turning postmortem findings into durable systemic improvements
Skilled at operating with ambiguity across large, complex system landscapes and driving alignment across multiple teams and stakeholders
