About Apple
Apple · Cupertino
AI Product Manager
10.7.2025
Description
This role will operate in both capacities, to augment existing AI roadmaps, as well as innovate and trailblaze 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:
- Own the end-to-end product lifecycle of Sales GenAI platform—from discovery and prioritization to delivery and optimization.
- Define and evolve a modular product vision that supports integration, web tools, insights emails, and agent-based decisioning.
- Translate business goals into clear AI/ML feature requirements in partnership with AI engineers and data scientists.
- Collaborate with UX/UI and engineering to ensure seamless integration of LLMs, RAG, and ML outputs into the GenAI gateway.
- Drive A/B testing, usage telemetry, and insights adoption metrics to inform roadmap decisions.
- Serve as the connective tissue between business partners and technical teams to balance impact and feasibility.
Qualifications
- 12+ years proven 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.
- 5+ years of product management experience, including 2+ in AI/ML or data-driven platforms. Experience launching AI-powered features in enterprise tools or data products.
- Ability to translate ambiguous business problems into concrete technical solutions.
- Ability to lead the development of AI projects from start to finish.
- Strong communication and storytelling skills with executive-level stakeholders.
- Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.
- Wide knowledge of GenAI and RAG strategies, micro services, MCP, A2E, recommendation systems, and prompt engineering.
- Deep understanding of LLM ecosystems (OpenAI, Anthropic, Gemini, etc.), RAG pipelines, vector databases (e.g., Pinecone, FAISS, Milvus, PostgreSQL).
- Experience with orchestration layers (e.g., LangChain, Semantic Kernel, Haystack), and prompt engineering best practices.
- Basic 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 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).
- Able to balance competing priorities, long-term projects, and ad hoc requirements.
- Ability to work in a fast-paced, dynamic, constantly evolving business environment.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, Applied Mathematics, Machine Learning, or a related field.
Preferred Qualifications
- Background in sales analytics, go-to-market, or operations.
- Ability to communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences.
- Experience working in dual-speed orgs where central and regional product needs coexist.
- Experience with anomaly detection and causal inference models.
- 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.
Benefits
MLjobs © 2025