Principal Software Architect, Finance Technology Platform
Principal architect role defining Apple's next-generation Finance Technology Platform: a multi-tenant, AI-native system where AI agents perform financial transaction processing end-to-end — ingestion, validation, approvals, settlement, and reconciliation — with humans in the loop by policy. Requires deep distributed-systems, event-sourcing, and production agentic-AI expertise.
- Compensation
- Not disclosed
- Location
- Sunnyvale
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Architecture
- Posted
Skills
Must have
- 10+ years of software engineering experience with deep expertise architecting large-scale distributed transactional systems
- Lead architect experience of a platform used by multiple engineering teams (multi-tenancy, extensibility, versioned APIs, configuration-driven behavior)
- Hands-on production experience building AI-native applications, including harness engineering: agent runtimes, tool/function calling, structured output validation, graph-based orchestration, context m
- Practical depth in the modern agentic stack — retrieval and vector search, embeddings, agent frameworks and graph orchestration, model evaluation and observability tooling, prompt/context engineering
- Experience designing evaluation, guardrail, and human-in-the-loop strategies for AI systems 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/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/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
- Demonstrated success mentoring and elevating technical talent across global teams
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience
Nice to have
- 15+ years of experience, with a portion architecting finance, accounting, or payments platforms at global scale
- Deep functional knowledge of financial lifecycles end-to-end (procure-to-pay, order-to-cash, record-to-report, expense, royalties, payouts, intercompany settlement), including approval hierarchies, ma
- Experience extending or decomposing monolithic enterprise systems into service-based platforms 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 — sandboxing, least-privilege tool access, injection defense
- 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, self-service onboarding
- Experience evolving engineering culture toward measurable reliability, correctness, cost ownership, and evaluation-driven AI development
Full 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.
Finance systems have historically been transaction recorders. We intend to build a platform that reasons. As Principal Software Architect, you will architect a platform where AI agents perform the majority of financial processing work end-to-end — interpreting business intent, validating and enriching transactions, routing approvals, matching and adjudicating documents, resolving exceptions, corresponding with counterparties, and preparing settlement — with humans in the loop by policy, not by default.
You will design the platform as a multi-tenant substrate: a shared canonical data model, orchestration engine, sub-ledger, accounting determination service, data layer, and reconciliation engine that multiple engineering teams build their own finance applications on top of, configuring behavior rather than rebuilding shared capability. Domain teams should onboard a new financial flow in weeks through configuration — not months through development.
You will influence architecture before code is written, own the standards that govern financial correctness and auditability, and be the senior technical voice partnering with Finance, Controllership, Tax, and Internal Audit leadership.
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.