AI Architect

Job Summary

Summary Posted: Aug 08, 2025 Weekly Hours: 40 Role Number: 20... Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish!Apples Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.Apple's US Decision Intelligence (DI) team is looking for a dedicated individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers. Were seeking a visionary US DI AI Platform Architect to lead the design and evolution of our internal AI orchestration layerpowering intelligent agents, embedding expert systems, and integrating GenAI capabilities across our sales data ecosystem. This role will work directly with product, engineering, and executive stakeholders to architect and scale a modular, future-proof AI infrastructure aligned with our AI strategy.

Description

Description This role will operate in both capacities, to augment existing AI roadmap, as well as innovate and trailblazing new frontier tech projects, crafting AI experiences that reduce time to insights and catalyze decision making.AI is a team sport, and in your role, you will be key in leading and influencing teams on the translation of business problems and questions into GenAI solutions. In this role, you will:- Architect the core GenAI orchestration platform, including routing logic, agent specialization, fallback handling, and metadata logging.- Design modular APIs, SDKs, and microservices to integrate LLMs, retrieval-augmented generation (RAG), traditional ML models, and data pipelines.- Drive interoperability with existing ML systems (e.g., forecasting, attribution, anomaly detection) and support downstream apps like dashboards, web tools, and chat interfaces.- Partner closely with data science, engineering, and sales ops to embed context-aware intelligence in decision-making tools.- Lead technical decision-making on infrastructure components, embedding safety mechanisms (e.g., autonomy sliders, grounding checks, model monitoring).- Build scalable pipelines for multi-modal agent input, memory, and semantic routing.- Contribute to hiring and mentoring a cross-functional team of engineers and scientists.- Collaborate closely with business teams to incorporate AI into their weekly cadences.

EEO Notice

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