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Digital RnD Decision Fabric (Agentic Workflows) Product Owner

Toronto, Canada Regular Posté le   May. 08, 2026 Expire le   Jun. 08, 2026 Salary Range   CAD 121,000.00 - 174,800.00
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Reference No. R2831956
Position Title: Digital R&D Decision Fabric Product Owner
Location: Toronto, ON

About the job

Are you ready to shape the future of medicine? Join Sanofi as the Digital RnD Decision Fabric Product Owner, where you will lead the vision and strategy for the RnD Decision Fabric. The decision fabric is a scalable agentic capability that connects data, analytics, AI models, and agents into unified decision-making workflows across RND. From portfolio prioritization, clinical trial design to resource allocation and risk assessment – all decisions are informed by near real-time internal and external data, predictive insights, and organizational knowledge.

As RnD Decision Fabric Product Owner, you'll be orchestrating the evangelization of the decision fabric that ensures consistency in how decisions are made across RnD, and ultimately accelerate our ability to bring life-changing medicines to patients by moving from ad-hoc decision-making to a more systematic, data-driven approach that amplifies and accelerates human expertise with AI capabilities. You will partner with business stakeholders, and development teams to refine the requirements for this foundational infrastructure that democratizes access to AI-powered decision support.


We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We are also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?

*Hybrid schedule - 3 days per week onsite required. *

Main Responsibilities:

  • Product Strategy & Execution: Lead the decision fabric's product vision and roadmap in collaboration with digital RND product, architecture, and AI platform teams.
  • Agent Capability Development: Define the functional scope for decision fabric agents and agentic workflows through cross-functional requirements discovery with RND stakeholders.
  • Change Leadership & Adoption: Champion decision fabric adoption across digital RND teams by developing and evangelizing best practices, guidelines, and standards.
  • Agent Lifecycle Management: Maintain a comprehensive inventory of all agents and agentic workflows to ensure discoverability, prevent duplication, and avoid agentic chaos.
  • Governance & Prioritization: Lead cross-RND governance forums to prioritize use cases, maximize synergies, and drive reuse across the decision fabric ecosystem.
  • Cross-Fabric Integration: Outline requirements for the integration between the decision fabric and data/analytics fabrics to enable comprehensive RND decision support capabilities.
  • Platform Capabilities: Work with the AI platform team to define core platform capabilities including connectivity, reusability, configurability, accessibility, security, and governance frameworks.

About you

  • MS – in Business, Science, Computer Science, or related field – required.
  • 10+ years’ experience in digital product management, with preferably experience in the Pharmaceutical Industry.
  • Experience or familiarity with the following are required:
    • Agents: Experience with designing, implementing, and scaling agentic AI workflows beyond proof-of-concept into production environments.
    • Agentic workflows: Functional understanding of agent design, including tool integration, orchestration patterns, and multi-agent coordination.
    • MCP servers: Functional understanding of MCP (Model Context Protocol) server design and tool development to connect agents with existing digital RND systems.
    • Governance Tools: Experience establishing agent lifecycle management practices, including versioning, inventory management, and reuse frameworks.
    • Decision Management Systems: Understanding of rules engines, business process management tools, and decision modeling standards.
    • DevOps for agentic workflows: Familiarity with productionizing agentic workflows, MCP servers to support agile development of decision support capabilities.
    • Cloud Platforms: Familiarity with major cloud services (AWS preferred)
    • Data Infrastructure: Familiarity with data lakes, warehouses, and pipelines (Snowflake, Databricks, AWS data infrastructure) to ensure the decision fabric has access to clean, reliable data.
  • Excellent communication, stakeholder engagement, and problem-solving skills.
  • Strategic problem-solver who can lead cross-functional discovery workshops and translate business requirements into technical solutions.
  • Proven track record managing cross-functional governance forums and driving organizational change initiatives.
  • Strong change management skills with experience championing new technologies and driving adoption across organizations.
  • Proven expertise in designing and implementing Agentic AI workflows, preferably supporting enterprise decision-making.
  • Experience connecting decision systems to data lakes, warehouses, and analytics fabrics (Snowflake, Databricks, or similar).
  • Master’s degree required.

Why choose us?

  • Bring the miracles of science to life alongside a supportive, future-focused team.
  • Discover endless opportunities to gain experience and drive your career, whether through promotion or international mobility
  • Enjoy a thoughtful rewards package that recognizes your contribution and amplifies your impact.
  • Take good care of yourself and your family with a wide range of health and wellbeing benefits, including at least 14 weeks’ gender-neutral parental leave.
  • Be part of a dynamic digital transformation journey with executive sponsorship and a strong innovative ecosystem.

This position is for a new vacant role that is now open for applications.

AI Usage

"Artificial Intelligence” refers to any systems that use automated processes, including algorithms and machine learning, to analyze data and make predictions, inferences, decisions, or recommendations without direct human involvement. These systems may process personal information to identify patterns, improve services, or support decision-making. The Company may use Artificial Intelligence for purposes including, but not limited to, resume screening and hiring, scheduling interviews or meetings, conducting surveys, matching skills with potential job openings, interview scoring, ensuring compliance with regulations applicable to our industry, and activities related to performance evaluation. Information collected and processed by the Company’s Artificial Intelligence systems may include the personal information detailed above and calendar availability. It excludes the information collected and processed for monitoring purposes. You should contact Human Resources if you have a question or concern regarding your personal information. You can also contact Canada’s Privacy Officer via Sanofi’s data subject request portal,  Data Subject Rights Webform. The Data Subject Rights Webform can also be used to request access or correction of your personal information and file a complaint.

Sanofi is an equal opportunity employer committed to diversity and inclusion. Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives. We welcome and encourage applications from all qualified applicants.  Accommodations for persons with disabilities required during the recruitment process are available upon request.

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All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here.

Toute compensation sera déterminée en fonction de l'expérience démontrée. Les employés peuvent être admissibles à participer aux programmes d'avantages sociaux de l'entreprise. Des informations supplémentaires sur les avantages sociaux peuvent être trouvées ici.

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La rémunération finale sera déterminée en fonction de l'expérience démontrée, des compétences, et autres facteurs objectifs. Les employés seront également éligibles aux programmes d'avantages sociaux de l'entreprise.

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