Apple
Worldwide Channel Sales & Operations - AI Product Manager, Conversational Commerce
πCupertino, California, United States
1 month ago
π 4 views
π₯ 0 clicked apply
1. AIML Product Strategy & Vision: - Define and drive the AI/ML product vision, strategy, and roadmap for conversational commerce solutions across our channel sales platforms. - Collaborate with cross-functional teams to understand business needs, customer struggles, and industry trends to shape a compelling product vision. - Translate business goals into technical requirements, driving the AI architecture needed to deliver scalable, ground breaking AI/ML solutions. 2. AI-POWERED SOLUTION: - Design AI/ML-driven features and solutions to create intelligent sales assistants. - Drive product development of intelligent systems that optimize personalized content delivery, and other AI-driven selling capabilities. - Oversee the integration of machine learning models into existing sales platforms and partner chatbots, better customer experiences to drive sales conversion.. 3. SCALABILITY & INNOVATION: - Architect solutions that are scalable, secure, and maintainable, using AI/ML to enable personalized shopping experiences and sales insights across multiple channels. - Stay on the cutting edge of AI/ML technologies, incorporating standard methodologies and innovations to continuously improve product offerings. - Build partnerships with external technology vendors and AI research institutions to stay ahead of trends and foster collaboration. 4. CROSS-FUNCTIONAL COLLABORATION: - Work closely with sales leaders, and partner teams, to ensure alignment on product requirements and value propositions. - Partner with data science, engineering, and program teams to ensure smooth execution from ideation to production. - Communicate the product vision, strategy, and value to partners and senior leadership, gaining alignment and support for AI/ML initiatives. 5. METRICS & PERFORMANCE: - Establish and monitor product success metrics (adoption, engagement, revenue impact) and use data-driven insights to drive continuous product improvement. - Manage and prioritize the product backlog, working with engineering teams to ensure timely delivery of high-impact features.