Sales - AI Integrations Engineer

Sales - Ai Integrations 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. Apple's Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.

Description

We're seeking a visionary DI AI Integrations Engineer to be the connective tissue between our GenAI agents and internal data & reporting systems. You'll build robust, secure, and scalable integrations that allow our LLM agents and insight tools to trigger actions, pull context, and operate across complex internal APIs and microservices. 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

Build and maintain integrations between legacy reporting tools with new LLM agents and enterprise APIs. Create 3 levels of integration, from lightweight integration through API endpoints, to fully deep integrations across Insights, Chat, and Summarization interfaces. Design secure, modular wrappers and service adapters for LLM workflows. Collaborate with AI Engineers and PMs to turn workflows into fully connected agent actions. Monitor performance and error handling for integration layers across multiple business units. Contribute to system design for observability, retries, and logging.

Minimum Qualifications

8+ years of experience in data and AI-related fields such as software architecture or AI engineering, software development, data science, data analysis, or data lead roles, with experience across both traditional ML systems and GenAI LLMs. We're looking for someone with an eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment. Working across global teams to ensure alignment of product roadmaps. Leverage existing AI service providers to leverage and reuse from other internal Engineering organizations. Applied knowledge of GenAI and RAG strategies, microservices, MCP, A2E, recommendation systems, and prompt engineering. Deep knowledge of LLM ecosystems (OpenAI, Anthropic, Gemini, etc.), RAG pipelines, vector databases (e.g., Pinecone, FAISS, Milvus, PostgreSQL). Proficiency in SQL and experience with at least one major data analytics platform, such as Hadoop, Spark, or Snowflake. Experience with API management, orchestration layers (e.g., LangChain, Semantic Kernel, Haystack), and prompt engineering best practices. Proficiency in programming languages, tools, and frameworks like Python, Git, Notebooks, Dataiku, and Streamlit. Familiarity with telemetry and evaluation frameworks for AI agents. Experience working with data science teams on insights generation using LLMs. Knowledge of project management, productivity, and design tools such as Wrike and Sketch. Strong time management skills with the ability to collaborate across multiple teams. Able to balance competing priorities, long-term projects, and ad hoc requirements. Ability to work in a fast-paced, dynamic, constantly evolving business environment. B.S. Degree in Computer Science/Engineering, or equivalent work experience

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. 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. 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.