Senior Product Manager, AI

AI Product Manager

The AI Product Manager is a strategic leader responsible for driving enterprise-wide adoption of AI technologies, enabling organizational productivity, and delivering measurable business impact through AI-driven solutions. This role integrates people, process, and technology to identify high‑value use cases, prioritize automation and AI opportunities, and deliver scalable AI products that support PMO, Engineering, and broader business transformation initiatives.

This role is central to shaping how the organization leverages Microsoft Copilot, automation platforms, workflow agents, and AI‑assisted productivity tools to modernize operations, accelerate delivery, and empower teams. The Product Manager partners with senior stakeholders, business units, IT, and cross‑functional teams to define and execute an AI roadmap aligned to corporate strategy.

The ideal candidate possesses a strong foundation in product management, a deep passion for AI‑led transformation, and hands‑on experience delivering intelligent solutions that improve efficiency, reduce manual effort, and elevate the employee experience.

• Own the AI product vision, roadmap, and execution strategy for enterprise-wide AI enablement.
• Translate business needs into AI use cases, workflows, agents, and automation opportunities.
• Ensure AI solutions drive value across PMO, Engineering, Operations, and business stakeholders.
• Evaluate and operationalize new AI capabilities (e.g., Copilot agent mode, workflow agents, data integrations).
• Lead the creation of an AI Innovation Workbook, AI catalogs, and recurring AI health/status reviews.
• Champion adoption of Copilot, workflow automation, intelligent document processing, and data‑driven tools.
• Experiment with emerging AI capabilities; run proofs‑of‑concept; scale successful solutions.
• Evangelize best practices for prompt engineering, agent design, automation patterns, and AI governance.
• Lead and mentor a team of analysts, product owners, and AI enablers working across PMO and engineering.
• Foster a culture of curiosity, innovation, experimentation, and continuous improvement.
• Set clear expectations, provide coaching, and support team career development.
• Partner with business leaders to identify opportunities for AI‑driven transformation.
• Act as the primary liaison between Engineering, PMO, IT, Data Platforms, and business partners.
• Gather, validate, and prioritize AI implementation requests from multiple stakeholder groups.
• Conduct user interviews, process mapping sessions, and AI maturity assessments.
• Prioritize use cases based on complexity, ROI, value creation, and business urgency.
• Define user personas, journeys, and success criteria for AI experiences.
• Lead the delivery of workflow agents, Copilots, dashboards, automations, and AI workflows.
• Coordinate cross‑functional teams including engineering, data, operations, and business analysts.
• Ensure AI solutions go from concept to MVP to enterprise scale successfully.
• Monitor AI solution performance, reliability, and adoption.
• Support incident response, risk mitigation, and change management.
• Ensure AI applications operate within required availability, security, and performance standards.
• Drive alignment between PMO leadership, engineering leaders, and enterprise stakeholders.
• Build AI adoption playbooks, training materials, release notes, and executive‑status updates.
• Facilitate “AI Weekly Status” meetings and reporting.
• Identify opportunities for automation and process enhancement across PMO and engineering.
• Champion a data‑driven culture using metrics, analytics, and AI usage insights.
• Introduce new efficiencies and reduce organizational manual effort by scaling AI capabilities.
• Track AI performance KPIs including time savings, productivity uplift, adoption, and cost avoidance.
• Build executive dashboards highlighting AI impact by function, workflow, and business value.
• Ensure each AI solution delivers measurable, repeatable returns.
• Ensure responsible AI usage aligned to enterprise standards, data privacy controls, and cybersecurity.
• Maintain documentation, models, and workflows within approved governance frameworks.
• Establish and enforce AI…