R&D Product Manager (m/w/x)

Introduction
The Data and AI on z/OS product management team is responsible for the entire Db2 for z/OS product portfolio which comprises the database itself (Db2 for z/OS) along with its supporting tools and utilities AI-related extensions like Db2 AI for z/OS SQL Data Insights and QMF and its analytics and hybrid cloud related extensions like Data Gate and Db2 Analytics Accelerator.

Your Role and Responsibilities
You are a Product Manager with some experience of successful product ownership and growth or experience in an adjacent role (development technical sales). Your peers would say you are trusted to consider customer outcomes business impacts and functional tradeoffs. You communicate in a way that leaves peers feeling respected heard and understood. At the same time the outcomes you deliver are crafted with the customer front of mind. You are eager to learn and extend your view about the market competition and products regularly.
You’ll be crucial in supporting sales and marketing initiatives to drive revenue growth. You will execute on product-led growth initiatives and develop business partners. Collaborating with cross-functional teams – including engineering business development sales and marketing – you’ll position the IBM Z Data and AI solutions in the broader context of key IBM initiatives. Work with development partners inside and outside IBM to create outcome-based roadmaps and define or refine product strategies.

Required Technical and Professional Expertise
Bachelor’s degree in Computer Science Engineering Artificial Intelligence or a related field.

• Understanding of product roadmaps end-to-end lifecycles release cadence and support.
• Experience in customer-driven usability and hypothesis-driven experimentation.
• A deep passion for innovation and creating data-backed solutions.
• Demonstrated ability to communicate with multiple stakeholders effectively.

Preferred Technical and Professional Expertise
Knowledge about IBM Z products technology and customers
Understanding of Data and AI strategy concepts key trends and competitors