AI Product Manager

Job Description

Job Description

Junior AI Product Manager
Job at a Glance
Title: Junior AI Product Manager
Location: Pittsburgh, Strongsville, Dallas
Contract: W2 only
Overview
We are seeking a Junior AI Product Manager to lead product planning, prioritization, and delivery coordination for enterprise AI capabilities across Microsoft 365, Copilot, Copilot Studio, connectors, and governed business automation. This role will partner with business stakeholders, architecture, engineering, security, data, and operations teams to define use cases, shape roadmaps, manage backlogs, and drive adoption of AI capabilities that deliver measurable business value.
Key Responsibilities

• Own product strategy, roadmap, and prioritization for AI worker capabilities across M365 and business application scenarios.
• Translate business demand into clear product requirements, epics, features, and acceptance criteria.
• Partner with architecture and engineering teams to align delivery with enterprise standards, governance, and security controls.
• Drive stakeholder engagement across LOB, platform, risk, compliance, and delivery teams.
• Manage backlog, dependencies, release planning, and outcome tracking.
• Define value realization metrics, adoption goals, and success measures for AI-enabled scenarios.
• Support connector onboarding, enterprise knowledge grounding, agent lifecycle planning, and use case intake.
• Coordinate pilot, rollout, and adoption activities across business and platform teams.

• Strong product management experience in enterprise platforms, digital workplace, automation, or AI-enabled programs.
• Experience translating business problems into scalable product capabilities and phased roadmaps.
• Familiarity with Microsoft 365, Copilot, Copilot Studio, Power Platform, enterprise search, and connector-based architectures.
• Strong communication, executive presentation, and cross-functional coordination skills.
• Experience with Agile delivery, backlog management, and requirements documentation.

• Experience with enterprise AI governance, prompt/agent lifecycle, or data access enablement.
• Financial services or regulated industry experience.
• Exposure to reporting and measurement of product adoption and business outcomes.