Associate Director, AI Product Management

Company: Novartis
Apply for the Associate Director, AI Product Management
Location: London
Job Description:

Overview

As Associate Director, AI Product Manager at Novartis, you lead the development, launch and ongoing improvement of AI-powered products to meet user needs and business goals. You collaborate with product owners and cross-functional teams to translate vision into a tangible roadmap, manage the product lifecycle, and drive success with data-driven decisions and ethical AI practices. You’ll navigate complexity with strategic action and stay ahead of external trends to maximize product value. This role supports impactful medicine initiatives in a hybrid London setting.

Pay / Benefits

  • insurance plans
  • retirement plans
  • wellbeing resources
  • global recognition programs
  • flexible and hybrid working options
  • minimum of 14 weeks paid parental leave

Responsibilities

  • Manage one or more AI-powered products depending on scale
  • Coordinate development, launch and refinement with business owners and cross-functional teams
  • Translate product vision, strategy and roadmap to align with user needs and objectives
  • Oversee product lifecycle from MVP to scale, guided by data-driven metrics
  • Monitor budget and resources to optimize ROI while keeping stakeholders engaged
  • Collaborate with DDIT and external partners to ensure smooth delivery and transition to maintenance
  • Track KPIs for process improvement, adoption, and stakeholder alignment
  • Ensure timely milestone delivery and efficient resource use

Key requirements

  • Bachelor’s degree in Computer Science, Engineering, Business or related field
  • 5+ years in life sciences with product management experience
  • Proven experience launching and scaling products from concept to market
  • Strong stakeholder management, process design and value realization capabilities
  • Experience supporting product strategy, development and continuous improvement
  • Experience working in both startup and enterprise environments
  • Stakeholder management
  • Change management
  • Learning agility
  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Deep Learning

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Posted: October 23rd, 2026