Apple's Sales organization needs to generate revenue to fuel product and service development, and this role aims to enhance that by crafting and implementing AI solutions that directly impact sales and customer experiences, reducing time to insights and catalyzing decision-making.
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
- Bring passion and dedication to your job
- Ability to lead development of AI Software from start to finish.
- Comfort with ambiguity.
- Strong time management skills with the ability to collaborate across multiple teams.
- Able to balance competing priorities, long-term projects, and ad hoc requirements.
