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. 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. In this role, you will: - 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.
- 7+ years of experience in ML, data engineering, or backend development, with recent focus on GenAI and LLMs.
- Eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment.
- Ability to lead development of AI projects from start to finish.
- Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.
- 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).
- Bias for action, curiosity, and a collaborative mindset.
- Familiarity with telemetry and evaluation frameworks for AI agents.
- Experience working with data science teams on insights generation leveraging 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.
- Proven experience designing scalable, cloud-native platforms (e.g., AWS, GCP, or on-prem hybrid).
- Ability 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.
- 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.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
