Agentforce Product Manager

ZipStaff•East Hanover, NJ

5d•Hybrid

About The Position

ZipStaff is seeking an Agentforce Product Manager for the US CRM organization at a global pharmaceutical company. You will own the enterprise Agentforce roadmap and backlog for governed AI agents that use Data Cloud (Data 360) as the trusted context layer, across marketing, sales, and later functions. This is a product-ownership seat with data fluency — not a Salesforce developer role and not a generic Agile PM role.

Requirements

5+ years in product management, AI product, CRM platform, automation, data platform, or enterprise SaaS.
Hands-on Salesforce Data Cloud and Agentforce, or a comparable enterprise AI and customer-data platform you can map to them.
AI product delivery: agent workflows, grounding and context, access control, evaluation, human oversight, and responsible AI governance.
Agile roadmap and backlog ownership across business, data, architecture, engineering, security, privacy, and risk.
Ability to explain AI constraints and dependencies to business and leadership.
Bachelor’s in data, technology, business, engineering, computer science, or a related field.
Ability to work hybrid in East Hanover, NJ (3 days on-site).
Must be legally authorized to work in the United States without sponsorship now or in the future.

Nice To Haves

Salesforce CRM, Data Cloud, Agentforce, APIs, workflow automation, and enterprise integration.
AI governance, agent evaluation, prompt and grounding design, monitoring, and incident management.
Pharma, life sciences, healthcare, or another regulated industry.
Advanced degree.

Responsibilities

Qualify Agentforce intake: user need, outcome, data context, risk, and reuse.
Set the Agentforce roadmap, reusable capability model, and sequencing from marketing and sales outward.
Prioritize by strategic value, readiness, governance risk, shared demand, data availability, and capacity.
Turn use cases into epics, features, stories, evaluation criteria, guardrails, and release plans.
Specify how unified profiles, Data Lake Objects, calculated insights, and permissions support agents, with the Data Cloud Product Owner.
Plan PI demand with Data Cloud, architecture, engineering, security, privacy, AI governance, and the delivery Center of Excellence.
Apply required reviews, data policies, agent guardrails, human oversight, and release conditions.
Define acceptance for grounding, access control, reliability, traceability, user experience, and human escalation.
Partner with change, training, and operations on adoption, and report value, quality, risk, and delivery health.