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Bottomlinetechnologiesvia Greenhouse

Senior Product Manager, AI & Data Science

IndiaPosted 6d ago
Data ScientistLeadFull-time

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About the Role

Why Choose Bottomline?

Are you ready to transform the way businesses pay and get paid? Bottomline is a global leader in business payments and cash management, with over 35 years of experience and moving more than $16 trillion in payments annually. We're looking for passionate individuals to join our team and help drive impactful results for our customers. If you're dedicated to delighting customers and promoting growth and innovation - we want you on our team!

Product Manager – AI & Data Science 

Location: Bangalore 
Experience: 6-8 years 
 

 

Role Summary 

We are seeking a Product Manager with strong AI & Data Science product experience to drive AI-led innovation across our product portfolio. This is a strategic AI product management role, focused on AI vision, governance, research, and prioritization—not day-to-day delivery or sprint execution. 

This PM will work horizontally across product lines, partnering with Product Line PMs and AI/Data Science/CTO engineering teams to ensure we invest in the right AI problems, apply responsible AI principles, and deliver high-impact, scalable AI features. 

 

Key Responsibilities 

AI Product Strategy & Roadmap 

  • Define and own the AI/Data Science product vision aligned to business outcomes. 
  • Identify and prioritize high-impact AI use cases across business payments network, corporate payment solutions and banking solutions 
  • Shape a multi‑quarter AI roadmap focused on measurable customer and business impact. 

AI Governance & Responsible AI 

  • Ensure AI initiatives comply with responsible AI principles (privacy, security, explainability, regulatory expectations). 
  • Establish and run AI intake, prioritization, and review mechanisms with Product Line PMs and engineering. 
  • Act as the central owner for AI product governance across teams. 

Research & Solutioning 

  • Lead problem discovery and solution research—customer pain points, data readiness, feasibility, and ROI. 
  • Share