Senior Product Manager - Enterprise AI

Job Title

Senior Product Manager, Enterprise AI

Job Summary

The Senior Product Manager, Enterprise AI is responsible for defining the vision, roadmap, and business outcomes for AI-powered products and experiences across the enterprise. This individual owns the product lifecycle from discovery through deployment and ongoing optimization, partnering with business stakeholders, engineering, data science, UX, compliance, and operations teams to deliver impactful AI solutions.

This role combines traditional product management responsibilities with deep knowledge of Generative AI, conversational AI, agent-based systems, machine learning, and AI governance. The Product Manager develops value hypotheses, prioritizes product investments, manages delivery roadmaps, defines acceptance criteria, measures outcomes, and ensures solutions meet regulatory, security, and risk management requirements.

The ideal candidate possesses a strong understanding of AI technologies and hands-on experience leading AI product development initiatives that deliver measurable business value.

Key Responsibilities

Product Strategy & Vision

• Define and communicate the vision, strategy, and roadmap for enterprise AI products and capabilities.
• Identify opportunities to leverage AI, automation, and conversational technologies to improve member, customer, provider, associate, or operational experiences.
• Develop business cases, value hypotheses, success metrics, and adoption strategies for AI initiatives.
• Balance business value, technical feasibility, risk, compliance requirements, and user experience in product prioritization decisions.

Product Ownership & Delivery

• Own and prioritize the product backlog, ensuring alignment to strategic objectives and customer needs.
• Lead product discovery efforts, including stakeholder interviews, journey mapping, business process analysis, and requirements gathering.
• Define product requirements, user stories, acceptance criteria, and release plans.
• Coordinate cross-functional teams through the full product lifecycle from concept, design, development, testing, launch, and continuous improvement.
• Manage scope, schedules, dependencies, risks, and resource requirements across multiple AI initiatives.
• Provide regular status updates and executive-level communications on roadmap progress, outcomes, and risks.

AI Experience Design

• Partner with conversation designers, engineers, and business stakeholders to design AI-powered experiences.
• Define conversational flows, intents, prompts, retrieval strategies, agent behaviors, and escalation paths.
• Determine when AI should respond autonomously and when interactions should be transferred to human support channels.
• Ensure AI experiences align with user needs, enterprise standards, and business objectives.

AI Quality, Evaluation & Governance

• Establish evaluation frameworks to measure AI performance, accuracy, safety, and business effectiveness.
• Design and oversee testing strategies including golden datasets, adversarial testing, regression testing, and user acceptance testing.
• Review conversation transcripts, feedback, and performance metrics to identify optimization opportunities.
• Define and monitor KPIs such as containment, task success rate, latency, accuracy, customer satisfaction, adoption, and business impact.
• Ensure compliance with enterprise AI governance, security, privacy, regulatory, and risk management standards.
• Partner with legal, compliance, security, and risk teams to implement responsible AI controls and governance processes.

Stakeholder Management

• Serve as the primary liaison between business stakeholders and technical delivery teams.
• Translate complex technical concepts into clear business outcomes and recommendations.
• Facilitate alignment among product, engineering, operations, analytics, compliance, and executive leadership teams.
• Influence decision-making through data-driven recommendations and customer-centric thinking.

Required Qualifications

• Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or a related field.
• 7+ years of professional experience, including at least 3 years in Product Management, Product Ownership, Program Management, or a related discipline.
• Experience leading AI, machine learning, conversational AI, or Generative AI initiatives from concept through production deployment.
• Strong understanding of AI product development, including LLMs, retrieval-augmented generation (RAG), prompt engineering, agent frameworks, model evaluation, and AI governance principles.
• Experience managing product roadmaps, backlogs, prioritization, and cross-functional delivery teams.
• Ability to define business outcomes, product success metrics, and measurable value realization strategies.
• Experience working with engineering, data science, UX, and business teams in Agile environments.
• Strong analytical, communication, and stakeholder management skills.
• Demonstrated ability to translate customer needs and business requirements into scalable product solutions.
• Passion for improving customer, provider, associate, or consumer experiences through technology and innovation.

Preferred Qualifications

• Experience with Conversational AI platforms, voice assistants, virtual agents, chatbots, or agentic AI systems.
• Hands-on experience with GenAI platforms such as Azure OpenAI, Microsoft Copilot, OpenAI, Anthropic, Google Vertex AI, or similar technologies.
• Experience developing AI evaluation frameworks, safety testing methodologies, and responsible AI controls.
• Experience in highly regulated industries such as healthcare, insurance, financial services, or utilities.
• Familiarity with HIPAA, privacy regulations, AI governance frameworks, and enterprise risk management practices.
• Experience managing third-party AI vendors and platform providers.
• Experience with Agile tools such as Jira, Azure DevOps, Confluence, and Figma.
• MBA or advanced degree preferred.

Success Metrics

• Delivery of AI products that achieve defined business outcomes and ROI targets.
• Adoption and engagement metrics for AI-enabled experiences.
• Improvements in customer or employee satisfaction.
• Reduction in operational effort through automation and AI capabilities.
• AI quality measures, including accuracy, safety, reliability, and compliance performance.
• Roadmap execution, on-time delivery, and stakeholder satisfaction.

This version positions the role as a true Enterprise AI Product Manager/Product Owner, focusing on owning outcomes, AI governance, conversational AI delivery, evaluation frameworks, roadmap ownership, and measurable business impact rather than a traditional IT product coordinator role.