Senior Software Engineer (GenAI SAP Finance), AI & Data Platforms (AiDP)

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world Join Apples Information Systems and Technology (ISu0026T) organization. ISu0026T is the engine behind everything Apple does for customers and for the people who build for them. Its Apples central nervous system. Supporting 2.5 billion active Apple devices processing billions of secure transactions and keeping the technology that defines modern life running flawlessly ISu0026T makes the impossible feel you love building solutions to handle global complexity and immense scale Imagine what you could do here. nnAI u0026 Data Platforms (AiDP) is ISu0026Ts engine for AI-powered innovation. The team brings together data application development and machine learning including generative AI along with data services and customer success functions to help ISu0026T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.

In the AiDP Finance team we build the Reporting and Analytical solutions to meet business need for Legal Management and Statutory Reporting. We source base data from SAP systems ECC RAR and S/4HANA and build ground-up native SAP HANA models to report on at near real time and at scale. We are now extending that foundation with generative AI. nnThis is a high-ownership senior individual-contributor role. We are seeking a seasoned engineer to define and lead this space combining deep knowledge of SAP Finance data with production GenAI technologies such as agentic frameworks MCP and RAG. You will shape how AI is applied across our Finance data platform the use cases the solution design and the standards working closely with our HANA engineering and GenAI platform teams to take them to production.

Own the solution architecture and roadmap for AI capabilities on our Finance data platform partnering with Finance and ISu0026T leadership to identify and prioritize high-value opportunities and to make the build-versus-buy and platform-selection decisions that follow. nnDefine the layer between GenAI platforms and our Finance models: the agent and tool framework MCP-based interfaces authentication and authorization and access to both real-time and historical data. nnArchitect conversational and natural-language experiences over financial data including natural-language-to-SQL against our native HANA models and define agentic skills that automate finance analysis and operational workflows end to a cross-functional team of engineers and analysts through mobilization roadmapping architecture review and release; represent the design to senior stakeholders and to Compliance Security and Internal Audit; and mentor engineers on the team.

10 years in the SAP domain with a significant focus on solution architecture for large-scale business-critical Finance track record owning a Finance platform end to end from use-case discovery and solution design through delivery adoption and continuous finance domain knowledge across revenue recognition order-to-cash and record-to-report and the reporting requirements of Legal Management and Statutory knowledge of SAP HANA data models and analytics on SAP-sourced data sufficient to define analytics strategy specify what the AI layer needs and partner credibly with HANA engineers on designing or delivering agentic systems and MCP-based integrations with hands-on depth in prompt engineering and SQL and Python skills for working with large financial or MS Degree or equivalent experience.

Deep understanding of revenue accounting including ASC 606 / IFRS 15 treatment and how RAR represents it at high contract and transaction knowledge of SAP Finance data including RAR and S/4HANA as a source system: data structures extraction interfaces and the business logic behind the or delivering an AI agent workflow or conversational experience in production grounded in enterprise setting technical direction and standards for engineering teams and influencing senior business and technology stakeholders without direct written and oral communication on technical and non-technical topics with the ability to articulate trade-offs to executive and diverse audiences.