Salesforce Product Manager - Agentforce & Data Cloud

Phoenix Oversight Group LLC•Arlington, VA

2d•Remote

About The Position

PhoenixTeam is hiring a Salesforce Product Manager to lead product strategy and delivery for Agentforce and Salesforce Data Cloud (now Data 360) for a commercial customer. The role owns the path from business problem to released capability, including use-case intake, data readiness, roadmap, backlog, solution definition, pilot, launch, adoption, measurement, and iteration. This is a hands-on platform product role for someone with prior delivery experience using both Agentforce and Data Cloud/Data 360. The Product Manager owns product decisions, prioritization, requirements, and success measures while partnering with Salesforce architects, administrators, developers, data engineers, and customer stakeholders. The role does not require being the primary configurator or developer, but does require technical fluency to make informed tradeoffs and maintain a high quality bar. The Product Manager will assess use cases, data and governance dependencies, and delivery readiness; define platform requirements and release plans; coordinate cross-functional stakeholders; and guide prototypes, pilots, testing, launches, and ongoing improvements. The position is full-time, W2, 100% remote within the U.S., and requires availability during core U.S. business hours for a 40-hour workweek. The start date is as soon as possible, with one opening.

Requirements

At least 5 years of product management or product ownership experience for enterprise software, CRM, data platforms, AI-enabled products, automation, or SaaS.
Demonstrated product management experience with both Salesforce Agentforce and Salesforce Data Cloud/Data 360, including taking Agentforce or Data Cloud capabilities through pilot or production release. Training or certification alone is insufficient.
Practical knowledge of Data Cloud/Data 360, including data ingestion or zero-copy access, data streams, Data Lake Objects and Data Model Objects, identity resolution, calculated insights, segmentation and activation, data quality, permissions, and governance.
Practical knowledge of Agentforce, including topics, instructions, actions, grounding or retrieval, Flow or API integrations, access controls, testing and evaluation, guardrails, human escalation, and monitoring.
Ability to own product strategy, roadmap, backlog, and release plan and write product requirements, user stories, acceptance criteria, and measurable success criteria for technical teams.
Strong Salesforce platform fluency, including the relationship among Salesforce applications, Flow, platform security and permissions, metadata, APIs, integrations, and enterprise data.
Experience coordinating decisions across business, architecture, data, engineering, security, privacy, legal, and operational stakeholders.
Strong judgment and communication skills, including ability to challenge low-value or poorly prepared use cases, explain technical tradeoffs clearly, and make prioritization decisions under ambiguity.

Nice To Haves

Salesforce Certified Agentforce Specialist and Salesforce Certified Data 360 Consultant (formerly Data Cloud Consultant).
Additional Salesforce credentials such as Platform Administrator, Business Analyst, Platform App Builder, Sales Cloud Consultant, or Service Cloud Consultant.
Experience with Salesforce Flow, MuleSoft or other API and integration patterns, Tableau or CRM Analytics, and enterprise data platforms such as Snowflake, Databricks, AWS, or Google Cloud.
Experience defining AI-agent evaluation, responsible-AI controls, prompt or grounding strategies, observability, incident response, and human-in-the-loop operating models.
Experience working in a Salesforce Center of Excellence, enterprise platform product team, or customer-facing consulting environment.
Experience driving adoption and operating-model change for new CRM, data, automation, or AI capabilities.

Responsibilities

Own the product vision, roadmap, priorities, and backlog for Agentforce and Data Cloud/Data 360 capabilities.
Manage intake and qualify use cases based on user need, business outcome, data availability, risk, reuse potential, cost, and delivery readiness.
Translate priorities into product requirements, epics, features, user stories, acceptance criteria, agent evaluation criteria, data requirements, and release plans.
Define Data Cloud/Data 360 requirements, including source systems, data streams and connectors, zero-copy access where appropriate, data-model mapping, identity resolution, calculated insights, segments and activations, unstructured content, permissions, consent, data quality, and governance.
Define Agentforce requirements, including topics, instructions, actions, grounding and retrieval, Flow and API integrations, access controls, guardrails, human handoff, and monitoring.
Prioritize work based on business value, data readiness, governance risk, technical dependencies, enterprise reuse, and delivery capacity.
Partner with business, architecture, data, engineering, security, privacy, legal, operations, and adoption teams to resolve dependencies and sequence releases.
Lead prototype, pilot, testing, and launch-readiness activities; define evaluation of groundedness, task completion, reliability, access control, escalation, user experience, and business impact.
Use production feedback and metrics to improve agent behavior, data quality, adoption, cost effectiveness, and reusable platform patterns.
Maintain clear decisions, assumptions, risks, and traceability from intended business outcome through data context, agent behavior, release, and measured result.