Principal Software Architect, Finance Technology Platform

Job description

We are seeking a Software Architect to define and lead the technical vision for Apple's next-generation Finance Technology Platform. This is a platform-defining technical authority role, responsible for designing and building a multi-tenant, AI-native platform that powers financial transaction processing end-to-end — from business event ingestion through validation, enrichment, approval, position tracking, settlement, and reconciliation. This is not a management role. It is a first-principles engineering leadership role: you will architect the platform, set the standards other teams build against, and personally shape the agentic Finance AI foundations that make this platform fundamentally different from the transaction-recording systems that came before it. Minimum Qualifications: 10+ years of software engineering experience, including deep expertise in architecting large-scale distributed transactional systems where correctness is non-negotiable. Demonstrated experience as the lead architect of a platform used by multiple engineering teams — multi-tenancy, extensibility, versioned APIs, and configuration-driven behavior. Hands-on experience building AI-native applications in production, including harness engineering: agent runtimes, tool/function calling, structured output validation, graph-based orchestration, context management, and memory systems. Practical depth in the modern agentic stack — retrieval and vector search, embeddings, agent frameworks and graph orchestration libraries, model evaluation and observability tooling, and prompt/context engineering at production scale. Experience designing evaluation, guardrail, and human-in-the-loop strategies for AI systems operating on consequential decisions. Strong foundation in event-driven and event-sourced architecture, saga/workflow orchestration, streaming platforms, change data capture, and transactional data stores. Experience with enterprise financial or transaction-processing domains — ledgers and sub-ledgers, payables, receivables, payments, settlement, or high-volume financial event processing. Experience building or integrating with ERP and financial systems of record, and with document and data ingestion formats and pipelines (EDI, cXML, OCR/document AI, CDC feeds). Experience with regulated, audited, or high-trust systems and their compliance implications. Track record of technical leadership and architectural influence across large, complex organizations. Exceptional ability to communicate complex technical concepts to executive, finance, and engineering audiences alike. Demonstrated success mentoring and elevating technical talent across global teams. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. Preferred Qualifications: 15+ years of experience, with a portion spent architecting finance, accounting, or payments platforms at global scale. Deep functional knowledge of one or more financial lifecycles end-to-end — procure-to-pay, order-to-cash, record-to-report, expense, royalties, partner or developer payouts, or intercompany settlement — including approval hierarchies, matching and tolerance frameworks, tax determination, payment terms, and period close. Experience extending or decomposing monolithic enterprise systems into service-based platforms that interoperate with the existing system of record, while the business ran uninterrupted. Experience designing sub-ledger and account-determination layers, multi-GAAP/statutory reporting, multi-entity and multi-currency processing, and intercompany netting. Experience with continuous reconciliation and break-management systems at scale. Experience building agentic systems that take real-world actions with money, contracts, or regulated data — including sandboxing, least-privilege tool access, and defense against injection via untrusted third-party documents. Experience with fine-tuning, distillation, or model routing to balance accuracy against cost and latency in production agent workloads. Experience with ML for finance: anomaly and fraud detection, cash forecasting, transaction classification, duplicate detection. Background in developer experience for platform consumers — SDKs, local test harnesses, simulation environments, and self-service onboarding. Experience evolving engineering culture toward measurable reliability, correctness, cost ownership, and evaluation-driven AI development.