Product Manager, AI Products & Agents
Key details
- Location
- Remote
- Work style
- Remote
- Level
- Senior
- Experience
- 5–8 yrs
- Function
- Product / Program management
- Focus area
- other
- Posted
- Yesterday
Skills
agileai agentsai evaluationai governanceazureazure devopsbacklog managementchange managementclaudecopilot studiocsmdesign thinkingfigmagenerative aijirallmmicrosoft 365miroobservabilityopenaipower platformproduct designproduct managementproduct strategyprototypingpsmragsafescrumuser research
About the role
Product Manager, AI Products & Agents
Information Technology | Global Scope | Reports to CIO
Position Summary
Diversified is seeking a Product Manager, AI Products & Agents to own the product lifecycle for internal AI products, AI agents, and agent-enabled experiences. Reporting directly to the CIO, this role will turn business problems into a prioritized AI product portfolio and guide solutions from discovery and prototyping through production, adoption, measurement, and continuous improvement.
This is a product leadership role that will define product vision and roadmaps, lead Agile delivery and Scrum ceremonies, apply design thinking and user-experience practices, manage the backlog, coordinate business and technical teams, and ensure each AI product has a clear user problem, accountable owner, measurable outcome, and responsible path to production.
Key Responsibilities
AI Product Strategy & Portfolio
Own the vision, roadmap, prioritization, and lifecycle for Diversified’s portfolio of internal AI products and AI agents.
Maintain a portfolio and product backlog covering proposed, active, piloted, production, scaled, and retired AI products.
Translate enterprise priorities and requirements into product hypotheses, features, user stories, and measurable outcomes.
Analyze investments using business value, user impact, feasibility, readiness, risk, reuse potential, and implementation effort.
Define build/buy/configure proposals in partnership with EA, s/w engineering, security, data, and business-system teams.
Product Discovery, Design Thinking & User Experience
Lead discovery workshops, stakeholder interviews, journey mapping, problem framing, and design-thinking sessions.
Define personas, user journeys, acceptance criteria, and target experiences for employees using AI-enabled products.
Prototype and test concepts with users before scaling; use feedback and observed usage to refine requirements and experience.
Design for appropriate human review, transparency, escalation, and handoffs when agents act on behalf of employees or interact with enterprise processes.
Agile Product Delivery & Scrum
Serve as product owner for AI products and agents, managing epics, features, user stories, acceptance criteria, and backlog.
Lead sprint planning, backlog refinement, demos, retrospectives, and release planning using Agile/Scrum practices.
Coordinate AI engineers, automation developers, data teams, architects, platform owners, security, and business SMEs.
Set clear definition-of-ready and definition-of-done expectations, including user validation, security, documentation, support, monitoring, and production-readiness requirements.
AI Agent Quality, Trust & Lifecycle
Define success criteria and evaluation plans for AI agents, including task completion, answer or action quality, user acceptance, reliability, latency, cost, and exception handling where applicable.
Partner with technical teams on agent evaluation, testing, observability, changes, retrieval quality, integrations, and monitoring.
Maintain clear ownership, dependencies, release history, risks, and lifecycle status for each AI product and agent.
Ensure responsible-AI, privacy, cybersecurity, access, data-governance, records, and compliance requirements are incorporated into product design and release decisions.
Adoption & Value Realization
Own launch readiness, communications, training approach, feedback loops, adoption plans, and post-launch product reviews.
Define and report product KPIs such as active usage, task completion, cycle-time improvement, quality, satisfaction, cost-to-serve, risk reduction, and financial impact where measurable.
Use telemetry, business outcomes, support data, and user feedback to improve, scale, pause, consolidate, or retire products.
Provide concise portfolio, roadmap, risk, and value updates to the CIO, AI governance forums, and business leaders.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Product Design, or equivalent practical experience.
5+ years of product management, product ownership, digital product, enterprise applications, or automation experience.
Demonstrated ownership from discovery and roadmap to delivery, adoption, measurement, and continuous improvement.
Strong Agile/Scrum skills, including roadmap, backlog, user stories, acceptance criteria, sprint planning, and demos.
Practical experience applying design thinking, human-centered design, journey mapping, prototyping, or UX practices.
Working knowledge of generative AI and AI-agent concepts sufficient to partner effectively with AI engineers, architects, data teams, security teams, and business stakeholders.
Strong executive communication, facilitation, prioritization, and cross-functional stakeholder-management skills.
Ability to manage multiple products and workstreams with clear decisions, dependencies, risks, and measurable outcomes.
Preferred Qualifications
Experience delivering enterprise generative-AI, conversational-AI, AI-agent, automation, or knowledge-assistant products.
Experience with Microsoft 365 Copilot, Copilot Studio, Power Platform, Azure AI services, Azure OpenAI, Anthropic/Claude, or comparable enterprise AI ecosystems.
Familiarity with RAG, LLM gateways/model routing, agent orchestration, APIs/integrations, tool use, evaluation frameworks, observability, and human-in-the-loop patterns.
Experience with Azure DevOps, Jira, Figma, Miro, or comparable product, development, and discovery tools.
Product, Agile, Scrum, design-thinking credentials such as CSPO/PSPO, CSM/PSM, SAFe Product Owner/Product Manager
Experience operating in a global, matrixed enterprise and partnering with executive stakeholders.
Key Skills
AI Product Management & Product Ownership
AI Agents / Agentic Product Experiences
Product Strategy, Roadmaps & Portfolio Prioritization
Agile, Scrum & Backlog Management
Design Thinking, User Research & UX
Product Discovery, Prototyping & Experimentation
AI Evaluation, Quality & Product Analytics
Responsible AI, Security & Governance Awareness
Business Process & Workflow Design
Change Management, Adoption & Value Realization
Executive Communication & Cross-Functional Leadership
Key Success Measures
A single, prioritized portfolio and roadmap for internal AI products and agents with clear owners, outcomes, lifecycle status, and dependencies.
Consistent product discovery, Agile delivery, user validation, and production-readiness discipline across AI initiatives.
Higher adoption and repeat usage of released AI products, supported by product telemetry and structured user feedback.
Documented business outcomes for production AI products, including productivity, quality, cycle time, customer/employee experience, cost, revenue, or risk outcomes where appropriate.
Fewer disconnected AI experiments through stronger reuse, prioritization, governance, and lifecycle decisions.
Why Join Us?
This role will help shape how Diversified turns AI ideas into trusted, usable products that improve how employees work and how the business operates. The Product Manager will have direct CIO sponsorship, enterprise-wide visibility, and the opportunity to establish the product discipline for a growing portfolio of AI products and agents.
Information Technology | Global Scope | Reports to CIO
Position Summary
Diversified is seeking a Product Manager, AI Products & Agents to own the product lifecycle for internal AI products, AI agents, and agent-enabled experiences. Reporting directly to the CIO, this role will turn business problems into a prioritized AI product portfolio and guide solutions from discovery and prototyping through production, adoption, measurement, and continuous improvement.
This is a product leadership role that will define product vision and roadmaps, lead Agile delivery and Scrum ceremonies, apply design thinking and user-experience practices, manage the backlog, coordinate business and technical teams, and ensure each AI product has a clear user problem, accountable owner, measurable outcome, and responsible path to production.
Key Responsibilities
AI Product Strategy & Portfolio
Own the vision, roadmap, prioritization, and lifecycle for Diversified’s portfolio of internal AI products and AI agents.
Maintain a portfolio and product backlog covering proposed, active, piloted, production, scaled, and retired AI products.
Translate enterprise priorities and requirements into product hypotheses, features, user stories, and measurable outcomes.
Analyze investments using business value, user impact, feasibility, readiness, risk, reuse potential, and implementation effort.
Define build/buy/configure proposals in partnership with EA, s/w engineering, security, data, and business-system teams.
Product Discovery, Design Thinking & User Experience
Lead discovery workshops, stakeholder interviews, journey mapping, problem framing, and design-thinking sessions.
Define personas, user journeys, acceptance criteria, and target experiences for employees using AI-enabled products.
Prototype and test concepts with users before scaling; use feedback and observed usage to refine requirements and experience.
Design for appropriate human review, transparency, escalation, and handoffs when agents act on behalf of employees or interact with enterprise processes.
Agile Product Delivery & Scrum
Serve as product owner for AI products and agents, managing epics, features, user stories, acceptance criteria, and backlog.
Lead sprint planning, backlog refinement, demos, retrospectives, and release planning using Agile/Scrum practices.
Coordinate AI engineers, automation developers, data teams, architects, platform owners, security, and business SMEs.
Set clear definition-of-ready and definition-of-done expectations, including user validation, security, documentation, support, monitoring, and production-readiness requirements.
AI Agent Quality, Trust & Lifecycle
Define success criteria and evaluation plans for AI agents, including task completion, answer or action quality, user acceptance, reliability, latency, cost, and exception handling where applicable.
Partner with technical teams on agent evaluation, testing, observability, changes, retrieval quality, integrations, and monitoring.
Maintain clear ownership, dependencies, release history, risks, and lifecycle status for each AI product and agent.
Ensure responsible-AI, privacy, cybersecurity, access, data-governance, records, and compliance requirements are incorporated into product design and release decisions.
Adoption & Value Realization
Own launch readiness, communications, training approach, feedback loops, adoption plans, and post-launch product reviews.
Define and report product KPIs such as active usage, task completion, cycle-time improvement, quality, satisfaction, cost-to-serve, risk reduction, and financial impact where measurable.
Use telemetry, business outcomes, support data, and user feedback to improve, scale, pause, consolidate, or retire products.
Provide concise portfolio, roadmap, risk, and value updates to the CIO, AI governance forums, and business leaders.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Product Design, or equivalent practical experience.
5+ years of product management, product ownership, digital product, enterprise applications, or automation experience.
Demonstrated ownership from discovery and roadmap to delivery, adoption, measurement, and continuous improvement.
Strong Agile/Scrum skills, including roadmap, backlog, user stories, acceptance criteria, sprint planning, and demos.
Practical experience applying design thinking, human-centered design, journey mapping, prototyping, or UX practices.
Working knowledge of generative AI and AI-agent concepts sufficient to partner effectively with AI engineers, architects, data teams, security teams, and business stakeholders.
Strong executive communication, facilitation, prioritization, and cross-functional stakeholder-management skills.
Ability to manage multiple products and workstreams with clear decisions, dependencies, risks, and measurable outcomes.
Preferred Qualifications
Experience delivering enterprise generative-AI, conversational-AI, AI-agent, automation, or knowledge-assistant products.
Experience with Microsoft 365 Copilot, Copilot Studio, Power Platform, Azure AI services, Azure OpenAI, Anthropic/Claude, or comparable enterprise AI ecosystems.
Familiarity with RAG, LLM gateways/model routing, agent orchestration, APIs/integrations, tool use, evaluation frameworks, observability, and human-in-the-loop patterns.
Experience with Azure DevOps, Jira, Figma, Miro, or comparable product, development, and discovery tools.
Product, Agile, Scrum, design-thinking credentials such as CSPO/PSPO, CSM/PSM, SAFe Product Owner/Product Manager
Experience operating in a global, matrixed enterprise and partnering with executive stakeholders.
Key Skills
AI Product Management & Product Ownership
AI Agents / Agentic Product Experiences
Product Strategy, Roadmaps & Portfolio Prioritization
Agile, Scrum & Backlog Management
Design Thinking, User Research & UX
Product Discovery, Prototyping & Experimentation
AI Evaluation, Quality & Product Analytics
Responsible AI, Security & Governance Awareness
Business Process & Workflow Design
Change Management, Adoption & Value Realization
Executive Communication & Cross-Functional Leadership
Key Success Measures
A single, prioritized portfolio and roadmap for internal AI products and agents with clear owners, outcomes, lifecycle status, and dependencies.
Consistent product discovery, Agile delivery, user validation, and production-readiness discipline across AI initiatives.
Higher adoption and repeat usage of released AI products, supported by product telemetry and structured user feedback.
Documented business outcomes for production AI products, including productivity, quality, cycle time, customer/employee experience, cost, revenue, or risk outcomes where appropriate.
Fewer disconnected AI experiments through stronger reuse, prioritization, governance, and lifecycle decisions.
Why Join Us?
This role will help shape how Diversified turns AI ideas into trusted, usable products that improve how employees work and how the business operates. The Product Manager will have direct CIO sponsorship, enterprise-wide visibility, and the opportunity to establish the product discipline for a growing portfolio of AI products and agents.
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