Apple's Sales organization needs to generate revenue to fuel product and service development. The US Decision Intelligence (DI) team is looking for an AI Software Engineer to build integrations between AI services and customer-facing platforms to improve decision-making and reduce time to insights for Apple Sales and its customers.
Requirements
- 8+ years of experience in Software Development, ML, and/or data science with recent focus on GenAI and LLMs.
- Strong JavaScript expertise. Experienced in Front-end development using React, and API development with Express.
- Experience building REST/GraphQL APIs and integrating with external services
- Proficiency in Python (FastAPI, LangChain, or similar frameworks), prompt engineering, and RESTful API design.
- Hands-on experience with LLM APIs, embeddings, vector databases, and RAG workflows.
- Solid grounding in data structures, async programming, and pipeline orchestration.
- Experience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).
Responsibilities
- 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.
- Develop and maintain services that embed GenAI capabilities into production systems.
- Own parts of the platform API layer connecting LLM agents with user-facing apps.
Other
- Eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment.
- Ability to lead development of AI Software from start to finish.
- Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.
- Strong time management skills with the ability to collaborate across multiple teams.
- Proven experience designing scalable, cloud-native platforms (e.g., AWS, GCP, or on-prem hybrid).
