Sr Manager, AI Solutions Technical Product Owner

Role Responsibilities

• Own the vision and roadmap for assigned AI products, maintaining a holistic and consistent roadmap across the product lifecycle from discovery through production and adoption.
• Ensure delivery: drive execution with agile product teams, hold the line on scope and priorities, push back where needed, and remove ambiguity between business intent and technical implementation.
• Translate business requirements into well-structured backlogs, user stories, and acceptance criteria for the technical team — and translate technical constraints, trade-offs, and progress back to business stakeholders.
• Operate fluently across the digital solution stack — distinguishing data products, AI data products, generative/agentic AI solutions, and full-stack applications — and guide teams and stakeholders on the right solution type for the problem.
• Understand and manage the implications of building for the enterprise: what separates a POC or MVP from a production-grade system in terms of architecture, compliance, security, scalability, and support model.
• Coordinate user acceptance testing (UAT), release, and production handover activities for digital products.
• Manage delivery through external vendor and contractor teams alongside internal engineering resources.
• Serve as the voice of the user on agile product development teams to maximize the value and impact of AI products.
• Prototype hands-on where it accelerates the team: use modern AI tools to produce POCs, mockups, or preliminary wireframes to convey product intent when a designer is not available.
• Drive adoption through user community engagement (e.g., roadshows, training sessions, knowledge sharing) and develop and maintain business-facing product documentation (value proposition, catalog, adoption metrics).
• Define, monitor, and achieve product success and value metrics.
• Coordinate with other product, platform, and data teams to ensure products fully integrate into the broader International Commercial analytics and AI ecosystem.

Basic Qualifications

• Bachelor's degree in a relevant discipline (Computer Science, Data Science, Engineering, Information Systems, Business, or a related field) and 7+ years of relevant experience in data, analytics, engineering, digital delivery, or product management.
• 2–3 years of hands-on product ownership or product management experience for digital, data, or AI products.
• Hands-on experience working in agile teams, processes, and practices.
• Proficiency with agile delivery tooling (e.g., Jira, Confluence), including backlog management, sprint ceremonies, and delivery documentation.
• Experience translating business requirements into structured backlogs, user stories, and acceptance criteria — and communicating in both directions between business and technical audiences.
• Experience coordinating UAT, release, and production handover for digital products.
• Experience managing delivery through external vendor or contractor teams.
• Demonstrated strength in delivery: track record of owning roadmaps, managing competing priorities, and shipping products through cross-functional teams.
• Solid understanding of the digital product development lifecycle, including the distinction between POC/MVP and enterprise-grade systems and its implications.
• Working fluency with modern AI tools, sufficient to independently build POCs, mockups, or preliminary wireframes.
• Experience with Snowflake or comparable modern cloud data platforms.
• Experience managing cross-functional stakeholder groups and effecting change; ability to influence without direct authority.
• Strong English communication skills (written and verbal).

Preferred Qualifications

• Advanced degree in a relevant discipline.
• Certification in agile or project management methodologies (e.g., Certified Scrum Product Owner, PMP, PRINCE2).
• Technical or engineering background (software development, data engineering, or data science experience).
• Experience with generative and agentic AI solutions and platforms.
• Pharma & Life Science commercial functional knowledge.
• Pharma & Life Science commercial data literacy.
• Deep domain expertise in an area of commercial, or demonstrated ability to translate expertise from another domain into the commercial space.

Non-Standard Work Schedule, Travel or Environment Requirements

• Flexibility in working hours is required to collaborate with international stakeholders across regions (e.g., Latin America, Europe, Asia — including markets such as Mexico, Brazil, Korea, and Japan). Occasional travel may be expected.

Organizational Relationships