JOB SUMMARY
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.
Required Qualifications
7+ of experience of 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 Qualifications
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.
