AI Engineer

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!

Apple's 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.

Description

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. We're looking for a hands-on AI Engineer with strong software development skills and a passion for applying LLMs and ML models to real-world business problems. You'll be responsible for building, testing, and optimizing intelligent agents, retrieval pipelines, and embedded AI features across our sales data platforms.

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.","responsibilities":"Architect Recommendation System based on agentic frameworks

Architect repository of images to support insights based on diffusion models

Architect agentic summarization framework for scalability

Architect RAG framework for scale

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

Preferred Qualifications

Strong experience articulating and translating business questions into AI solutions.

Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences.

Experience with anomaly detection and causal inference models.

Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership.

Proven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.).

Familiarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs.

Proficiency with other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred.

Advanced Degree (MS or Ph.D.) in Economics, Electrical Engineering, Statistics, Data Science, or a similar quantitative field is preferred.

Minimum Qualifications

7+ years of experience in ML, data engineering, or backend development, with recent focus on GenAI and LLMs.