Agent force Product Manager

Job Purpose

Client is on a mission to transform medicine and improve lives worldwide. As a global leader in healthcare we leverage advanced technology and data to deliver patient-centric solutions enhance customer engagement and drive innovation. We collaborate closely with the US business bringing insights and challenging ideas to empower smarter data-driven decision-making. The US CRM organization sits within Strategy Platforms & Transformation (SPT) AI & Platform Products and plays a crucial role in driving the transformation to a next-generation Customer360 operating model.

We seeks an accomplished product leader with a track record of turning business demand from multiple commercial functions into a well-managed data product backlog. Strong prioritization judgment stakeholder partnership and hands-on data fluency are essential to success in this role.

Reporting to Director PO Audience Activation & Marketing Intelligence Agentforce Product Manager owns the enterprise Agentforce capability roadmap and backlog for governed AI agents that use Data 360 as a trusted context layer. The role manages intake and prioritization defines reusable agent patterns and guardrails coordinates Data Cloud and AI dependencies and works with enterprise AI governance the DDIT Center of Excellence and architects to build validate release and operate Agentforce capabilities responsibly across marketing sales and future functional areas.

Major Accountabilities

• Manage Agentforce intake: Receive and qualify requests for Agentforce capabilities and features that leverage Data 360 documenting the user need intended outcome data context risk and enterprise reuse potential.
• Set capability strategy and roadmap: Define the Agentforce roadmap reusable capability model and sequencing across initial marketing and sales use cases and future functional areas.
• Prioritize enterprise demand: Prioritize support and platform capabilities using strategic value readiness governance risk shared demand data availability and delivery capacity.
• Own and refine the backlog: Translate prioritized use cases into epics features user stories evaluation criteria guardrails and release plans for Agentforce capabilities.
• Define governed context patterns: Partner with the Data Cloud Platform Product Owner to specify how unified profiles Data Lake Objects calculated insights permissions and other governed data context will support agents.
• Coordinate PI planning: Plan Agentforce demand and dependencies with Data Cloud architecture engineering security privacy AI governance and DDIT delivery teams.
• Embed responsible AI governance: Liaise with Nova OS and DDIT AI Governance to apply required reviews documentation data policies model and agent guardrails human oversight and release conditions.
• Lead delivery with the Center of Excellence: Work with DDIT Center of Excellence teams and architects to design build test release and support reusable Agentforce capabilities.
• Validate quality and safety: Define acceptance and evaluation criteria for functional performance grounding access control reliability traceability user experience and appropriate escalation to humans.
• Drive adoption and learning: Partner with change training operations and business leads to support adoption; capture feedback and operational evidence for iterative improvement.
• Measure and communicate impact: Track business value adoption quality risk and delivery health; communicate decisions limitations and outcomes transparently to stakeholders and governance bodies.

Key Performance Indicators

KPI area What good looks like

• Business value Agentforce releases demonstrate outcomes against agreed use-case KPIs and user needs.
• Responsible AI compliance Required governance reviews guardrails evidence and release conditions are complete and traceable.
• Agent quality Capabilities meet agreed evaluation criteria for grounded outputs access control reliability and human escalation.
• Roadmap and backlog health Enterprise Agentforce demand is prioritized clearly specified and aligned to Data Cloud and AI dependencies.
• Adoption and trust Target users adopt released capabilities and provide actionable feedback on usefulness clarity and control.
• Reuse and scalability Shared agent patterns data context and controls support multiple use cases without unnecessary duplication.

Ideal Background(Must Have)

• Bachelors degree in data technology business engineering computer science or a related field required; advanced degree preferred.
• Fluent English; other languages are desirable.
• 5 years of product management AI product CRM platform automation data platform or enterprise SaaS experience.
• Strong understanding of AI-enabled product delivery agent workflows grounding and context access controls evaluation human oversight and responsible AI governance.
• Hands-on knowledge of Salesforce Data Cloud and Agentforce or comparable enterprise AI and customer data platforms.
• Demonstrated ability to manage an agile roadmap and backlog across business Data Cloud architecture engineering security privacy legal risk and AI governance stakeholders.
• Excellent communication skills and the ability to translate AI opportunities constraints risks and technical dependencies for business and leadership audiences.

Preferred

• Experience with Salesforce CRM Data Cloud Agentforce APIs workflow automation and enterprise integration patterns.
• Familiarity with AI governance frameworks model or agent evaluation prompt and grounding design monitoring and incident management.
• Background in pharma life sciences healthcare or another regulated industry where privacy trust and controlled technology use are essential.

Leadership Competencies

Navigate complexity

• Enable impactful and timely decision-making across business data technology privacy and compliance stakeholders.
• Identify the critical issues in complex situations maintain focus on enterprise outcomes and adapt priorities as conditions change.
• Take a long-term view of platform sustainability downstream impacts and reusable enterprise capabilities.

Deliver collective impact

• Integrate diverse perspectives to achieve the best outcome for the enterprise.
• Influence without authority and collaborate effectively across organizational boundaries.
• Challenge assumptions constructively and make decisions grounded in evidence.