Job Summary
We are seeking an experienced Product Owner / Product Manager to lead the end‑to‑end lifecycle of Enterprise AI and GenAI products. This role is responsible for product discovery, requirements definition, roadmap development, and delivery of AI‑enabled solutions that drive measurable business value.
The ideal candidate combines strong product management expertise, a solid understanding of AI / GenAI concepts, and the ability to collaborate effectively across business stakeholders, UX, data science, engineering, and governance teams. This role operates in a hybrid work model with day‑shift alignment and no regular travel required.
Core Role Profile
• Primary Role: Product Manager / Product Owner for Enterprise AI products
• Focus Mix:
○ ~70–75% Product discovery, strategy, requirements, and delivery
○ ~10% Program, governance, and compliance coordination
○ Remaining time supporting UX collaboration and rapid prototyping
Key Responsibilities
1. Product Discovery & Service Design
• Partner with business users to understand current workflows, systems, data, and pain points
• Conduct discovery and service design exercises to identify AI and non‑AI solution opportunities
• Translate business problems into clearly defined product opportunities
• Map opportunities to appropriate AI and supporting technologies at a high level
2. Rapid Prototyping & UX Collaboration
• Utilize AI‑assisted and low‑code prototyping tools to:
○ Generate and refine product requirements
○ Create high‑fidelity interactive prototypes and UI mockups
• Collaborate closely with UX designers to iterate on designs and improve user experience
• Use prototypes primarily to communicate intent, validate concepts, and gain stakeholder buy‑in
3. Product Strategy, Value & ROI
• Define product value propositions and success metrics
• Develop high‑level ROI assessments, including:
○ Efficiency and FTE savings
○ Cost reduction opportunities
○ Revenue or value generation potential
• Ensure product decisions align with enterprise priorities, governance standards, and ethical AI considerations
4. Product Design, Roadmap & Delivery
• Own detailed requirements gathering, including data mapping and sample data definition
• Work closely with:
○ Data scientists
○ Architects
○ Engineering teams
• Define and manage:
○ Product roadmaps (MVP through post‑MVP scaling)
○ Epics, features, and user stories
○ Backlog prioritization and sprint planning
• Leverage Agile delivery practices while ensuring enterprise transparency and governance
5. AI Model & Evaluation Ownership
• Support LLM and model selection, provisioning, and use‑case alignment
• Define and oversee model evaluation strategies, including:
○ Universal metrics (accuracy, latency, hallucination risk, completeness)
○ Use‑case‑specific performance criteria
• Partner with model evaluation, risk, and governance teams to ensure responsible AI adoption
6. Testing, Launch & Ongoing Operations
• Coordinate testing efforts with QA, business users, and technical teams
• Support production readiness, rollout planning, communications, and training
• Post‑launch:
○ Monitor AI solution performance in production
○ Track outcomes against defined success metrics
○ Drive continuous improvement and roadmap execution
Required Skills & Experience
• Strong experience as a Product Manager or Product Owner delivering enterprise products
• Solid understanding of AI / GenAI concepts, use cases, and lifecycle considerations
• Proven ability to work across business, UX, data, engineering, and governance teams
• Experience with:
○ Requirements discovery and lifecycle management
○ Roadmap definition and backlog management
○ Agile delivery frameworks
• Comfort navigating enterprise governance, risk, and compliance processes
• Excellent communication, stakeholder management, and facilitation skills
• Ability to operate effectively in a hybrid work environment
Nice to Have Skills
• Background in data science, engineering, or software development
• Prior experience in healthcare or regulated industries
• Hands‑on exposure to AI‑assisted prototyping or low‑code tools
• Experience with enterprise AI monitoring and evaluation frameworks
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