AI Product Manager

Role Description

Define, prioritize, and deliver AI and GenAI products that solve high-value business problems while satisfying enterprise requirements for risk, security, compliance, usability, adoption, and operational readiness. The role connects business strategy with AI capabilities and measurable outcomes.

Primary ownership

• AI product vision, roadmap, use-case prioritization, business case, and success metrics.
• Product discovery, MVP definition, pilot planning, adoption, measurement, and lifecycle management.
• Cross-functional delivery alignment across business, AI engineering, research, architecture, risk, compliance, legal, cybersecurity, and UX.

Key responsibilities

• Define product vision, strategy, roadmap, and success metrics for AI and GenAI products across business and enterprise functions.
• Identify and prioritize use cases based on value, feasibility, data readiness, risk profile, user impact, and strategic alignment.
• Translate business needs into product requirements, user stories, acceptance criteria, operating requirements, and measurable outcomes.
• Manage product lifecycle from discovery, experimentation, MVP, pilot, production rollout, adoption, monitoring, and continuous improvement.
• Partner with AI engineers, researchers, data teams, architects, UX, risk, compliance, legal, cybersecurity, and business stakeholders.
• Define KPIs such as adoption, productivity gain, cost reduction, cycle-time reduction, accuracy, risk reduction, user satisfaction, and operational efficiency.
• Ensure AI products include appropriate governance, human oversight, explainability, auditability, and Responsible AI controls.
• Drive user adoption through change management, training, communication, feedback loops, and executive reporting.

Qualifications

• 7+ years of experience in product management.
• Experience in product management, digital transformation, AI/ML products, data platforms, enterprise technology, or business transformation.
• Strong understanding of AI, GenAI, LLM capabilities, limitations, risks, and enterprise adoption considerations.
• Ability to translate business problems into AI-enabled product opportunities and measurable outcomes.
• Experience working with engineering, data science, research, architecture, risk, compliance, and business stakeholders.
• Strong roadmap management, prioritization, stakeholder engagement, business-case development, and delivery-governance skills.

Preferred experience

• Banking, financial services, fintech, risk, operations, compliance, customer service, or enterprise productivity background.
• Experience delivering AI copilots, knowledge assistants, automation tools, analytics products, AI platforms, or data products.
• Familiarity with AI governance, model risk, data privacy, cybersecurity, and Responsible AI requirements.

Benefits

• Medical, dental, and vision insurance.
• Flexible spending or health savings account.
• Life and AD&D insurance.
• Short-and long-term disability coverage.
• Paid time off.
• Employee assistance.
• Participation in a 401k program with company match.
• Additional voluntary or legally required benefits.