AI Product Manager

Volvo CarsMahwah, NJ
Onsite

About The Position

AI is central to Volvo Cars’ digital transformation. This role ensures that AI investments translate into scalable, trusted, and business-ready products—bridging strategy, engineering, and real-world application across customer, retailer, and operational experiences.

Requirements

  • 5+ years of experience in product management roles with a proven track record of delivering AI, ML products end to end
  • Experience in product management with responsibility for strategy, roadmap, and delivery of digital or data-driven products
  • Strong understanding of machine learning, advanced analytics, and Generative AI including large language models
  • Experience delivering AI or ML solutions in production environments
  • Proven ability to build business cases, define OKRs, and measure product performance
  • Experience working in cross-functional environments, collaborating with engineering, data science, and business stakeholders
  • Excellent communication and executive presentation skills
  • Experience with cloud and data platforms; strong knowledge of Snowflake and Azure is required
  • Knowledge of data and AI governance and best practices, as well as responsible frameworks, and data privacy regulations

Nice To Haves

  • experience with Snowflake Cortex and Azure AI Foundry is highly preferred

Responsibilities

  • Define and own the AI product strategy and roadmap, aligning with business priorities and customer and retailer needs
  • Identify, prioritize, and shape AI use cases and capabilities across key digital touchpoints including web, mobile, connected car, and retailer platforms
  • Lead the end-to-end delivery of AI, ML, and advanced analytics initiatives, from ideation to evaluation and execution, and through delivery and end user adoption
  • Translate business needs into clear, well defined AI requirements, user stories, test cases, and ultimately products in production
  • Coordinate with cross functional teams across data, engineering, analytics, and business stakeholders
  • Establish and manage roadmaps, timelines, milestones, and success metrics, ensuring delivery against measurable outcomes
  • Drive adoption, usability, and trust, ensuring AI outputs are explainable and embedded into business processes
  • Champion a test and learn approach, enabling rapid experimentation and iteration
  • Ensure alignment with AI governance, data privacy, and responsible AI standards
  • Communicate AI strategy, progress, and outcomes to senior leadership and global stakeholders
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