Apple's US Decision Intelligence (DI) team is looking to craft, implement, and operate AI solutions that have a direct and measurable impact on Apple Sales and its customers, by designing and evolving an internal AI orchestration layer to power intelligent agents, embed expert systems, and integrate GenAI capabilities across the sales data ecosystem.
Requirements
- 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.
- 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.
Responsibilities
- 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.
Other
- B.S Degree in Computer Science/Engineering, or equivalent work experience.
- Strong time management skills with the ability to collaborate across multiple teams.
- Ability to work in a fast-paced, dynamic, constantly evolving business environment.
- Able to balance competing priorities, long-term projects, and ad hoc requirements.
- Strong experience articulating and translating business questions into AI solutions.
