Digital RnD Decision Fabric (Agentic Workflows) Product Owner

About the role

The Digital RnD Decision Fabric Product Owner will lead the vision and strategy for the RnD Decision Fabric, a scalable agentic capability that connects data, analytics, AI models, and agents into unified decision-making workflows across RND. This role involves leading the product vision and roadmap, defining agent capabilities, championing adoption, managing the agent lifecycle, leading governance forums, and outlining requirements for platform capabilities.

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.

Requirements

• 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.
• 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.

Qualifications

• 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).
• Masters degree required.

Skills

• Experience with Agents, Agentic Workflows, MCP Servers, Governance Tools, Decision Management Systems, DevOps for Agentic Workflows, Data Infrastructure.

Benefits

Details about benefits are available upon request.

Pay

Compensation is determined commensurate with demonstrated experience.

Schedule

Hybrid schedule - 3 days per week onsite required.