Product Manager

RSM US LLP•Nashville, TN

4d•$111,200 - $190,300•Hybrid

About The Position

The Product Manager / Product Owner is accountable for the vision, roadmap, prioritization, adoption, and measurable business value of assigned AI-enabled digital products used by Consulting professionals and clients. The role owns the “what,” “why,” and business value of assigned products or product families, establishing product strategy and roadmaps, prioritizing investments, evaluating outcomes, and ensuring products meet users’ needs. It serves as the primary connection between the Digital Products function and Consulting delivery leadership, translating business needs into product priorities and supporting organizational alignment and sustained value realization. This is a hands-on product leadership role requiring mid-to-advanced proficiency with agentic AI tools such as Microsoft Copilot, ChatGPT, Claude, MCP-connected tools, prototyping tools, and automation agents. The Product Manager uses these capabilities to create repeatable workflows, prototype solutions, develop and refine requirements, analyze complex information, automate product tasks, test ideas, and accelerate product decisions and delivery. The role partners with engineering and platform teams to deliver releases, and with change and adoption teams to drive utilization and value realization. Most roles at RSM follow a hybrid workstyle, with team members aligned to an RSM office and meeting in person when it best supports clients, teams, development, or relationship-building. Some roles may be virtual or primarily on-site based on role requirements, team priorities, and client needs. Compensation ranges from $111,200 to $190,300. Selected candidates are eligible for a discretionary bonus based on firm and individual performance.

Requirements

At least 5 years of experience in a Product Manager, Product Owner, AI product, digital product, or similar role.
Mid-to-advanced hands-on proficiency with agentic AI tools such as Microsoft Copilot, ChatGPT, or Claude, with examples of using them beyond basic research and content drafting to create multi-step or repeatable workflows, develop prototypes, improve requirements and acceptance criteria, analyze and synthesize complex information, automate product-management activities, and measurably improve product outcomes.
Ability to critically evaluate AI output, iterate effectively, and apply appropriate judgment concerning accuracy, privacy, security, governance, and human oversight.

Nice To Haves

Consulting or professional services experience, especially with ERP/CRM/HCM implementation or delivery operations.
Experience product managing AI-enabled, internal platform, knowledge retrieval, RAG, MLOps, MCP-enabled integration, automation, or agentic workflow products.
Ability to evaluate where AI should and should not be used while balancing user value, adoption, risk, data privacy, governance, and quality controls.
Working understanding of Model Context Protocol concepts, including tools, connectors, agents, context sources, permissions, and governance considerations.
Curiosity and an experimentation mindset with emerging AI tools, including learning quickly, testing workflows, and translating lessons into scalable product practices.
Experience owning product backlogs in Agile/Scrum or hybrid delivery models.
Experience writing epics, features, user stories, acceptance criteria, and release acceptance plans.
Experience using ADO, Jira, Aha!, Productboard, or similar product/backlog tooling.
Experience measuring digital product adoption, operational value, ROI, and product health.
Professional certifications related to product management, business applications, agile delivery, organizational change management, or relevant technology platforms are encouraged.

Responsibilities

Own and maintain the product backlog, including epics, features, user stories, acceptance criteria, prioritization, and backlog health.
Own product vision, strategy, roadmap, lifecycle decisions, and prioritization for assigned products.
Be accountable for adoption outcomes and partner with Change Management on training, communications, readiness, launch, and hypercare plans.
Use AI tools, agentic workflows, and MCP-enabled integrations to build repeatable product workflows; develop and refine requirements; create prototypes and proofs of concept; analyze backlogs and complex information; automate routine product tasks; synthesize stakeholder input; and accelerate product decisions and delivery.
Identify opportunities to embed AI, automation, knowledge retrieval, and agentic experiences into products to improve user outcomes, delivery efficiency, or measurable business value.
Partner with engineering and platform teams to determine how MCP servers, tools, and connectors can securely expose enterprise systems, product data, documents, workflows, or operational context to AI agents.
Rapidly prototype product concepts, workflows, prompts, wireframes, or proof-of-concept experiences to validate assumptions before committing engineering capacity.
Prepare Product Council recommendations for investment, scaling, sustainment, and retirement decisions.
Make day-to-day product prioritization and backlog tradeoff decisions within approved roadmap, funding, risk, and capacity guardrails.
Maintain current knowledge of industry trends, emerging technologies, AI capabilities, MCP-enabled integration patterns, agentic workflows, product management disciplines, responsible AI practices, and relevant business application ecosystems.