Product Managers play a pivotal role in shaping offerings that leverage artificial intelligence machine learning and data analytics to solve complex business challenges. IBM follows a structured product lifecycle management process integrating agileĀ methodologiesĀ data-informedĀ decision-making andĀ cross-functionalĀ collaboration.Ā Product Managers work across engineering design data science and go-to-market teams to deliver innovative secure and scalable AI-powered solutions.
The responsibiliti es of a Product Manager include:
-Define and drive product strategy for AI and data-centric offerings aligning with business goals and user needs.
-Collaborate with cross-functional teams including data scientists engineers designers and stakeholders to deliver high-quality features and models.
-Translate complex technical capabilities (e.g. ML models data pipelines APIs) into clear product requirements and user stories.
-Prioritize product backlog using data-driven frameworks and ensure alignment with roadmap and KPIs.
-Facilitate ethical AI practices by integrating fairness transparency and compliance into product development.
-Monitor product performance using analytics tools and user feedback to iterate and improve continuously.
-Communicate product vision strategy and progress to internal and external stakeholders including executives and customers.
-Champion user experience and usability in AI interfaces ensuring intuitive and trustworthy interactions.
-Strong product management fundamentals: roadmap planning backlog grooming stakeholder alignment and go-to-market execution.
-Understanding of AI/ML concepts data lifecycle and model deployment practices.
-Experience with Agile methodologies including sprint planning retrospectives and iterative delivery.
-Proficiency in product analytics tools and data visualization platforms
-Strong communication and storytelling skills to translate technical insights into business value.
-Ability to manage dependencies across teams and anticipate risks in product delivery.
-Experience with enterprise AI products or platforms
-Exposure to AI ethics frameworks and responsible AI practices.
-Comfortable working with global teams across time zones and cultures.