AI Product Manager

Onlu GC and USC (Who can work on w2 or has own corp , No 1099)

AI Product Manager

Jersey City, NJ

Contract

Role purpose

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, AIRP platform capabilities, citizen development, and measurable outcomes.

Client-specific emphasi

s· This is primarily AI for business, with use cases spanning KYC, credit underwriting, governance tracking, pitch book generation, Banker 360, Customer 360, deal library intelligence, financial crime quality, and sanctions screening

.· The Product Manager should understand AIRP as the enterprise AI-ready platform and coordinate with engineering on AWS, Terraform/IaC, DevOps pipelines, security, and governance dependencies

.· Responsible citizen development through Power Platform, Copilot Studio, Power Apps, Power Automate, and Power BI is part of the AI-native bank agenda and should be reflected in adoption and roadmap planning

.Primary ownershi

p· AI product vision, AIRP roadmap alignment, use-case prioritization, business case, and success metrics

.· Product discovery, MVP definition, pilot planning, production rollout, adoption, measurement, and lifecycle management

.· Cross-functional delivery alignment across business, AI engineering, research, AIRP platform, cloud engineering, risk, compliance, legal, cybersecurity, data, UX, and citizen-development teams

.

Key responsibiliti

es· Define product vision, strategy, roadmap, and success metrics for AI and GenAI products across business and enterprise function

s.· Identify and prioritize use cases based on value, feasibility, data readiness, risk profile, platform readiness, AWS/cloud dependencies, user impact, and strategic alignmen

t.· Translate business needs into product requirements, user stories, acceptance criteria, operating requirements, governance requirements, and measurable outcome

s.· Manage product lifecycle from discovery, experimentation, MVP, pilot, production rollout, adoption, monitoring, and continuous improvemen

t.· Partner with AI engineers, researchers, cloud/platform teams, architects, UX, risk, compliance, legal, cybersecurity, data owners, and business stakeholder

s.· Define KPIs such as adoption, productivity gain, cost reduction, cycle-time reduction, accuracy, risk reduction, user satisfaction, operational efficiency, and control effectivenes

s.· Ensure AI products include appropriate governance, human oversight, explainability, auditability, security, data privacy, and Responsible AI control

s.· Drive AI-native adoption through change management, training, communication, feedback loops, executive reporting, and responsible citizen-development enablemen

t.

Must-have candidate prof

ile· Experience in product management, digital transformation, AI/ML products, data platforms, enterprise technology, or business transformati

on.· Strong understanding of AI, GenAI, LLM capabilities, limitations, risks, and enterprise adoption consideratio

ns.· Ability to translate business problems into AI-enabled product opportunities, roadmaps, requirements, and measurable outcom

es.· Experience working with engineering, data science, research, architecture, risk, compliance, cybersecurity, legal, and business stakeholde

rs.· Strong roadmap management, prioritization, stakeholder engagement, business-case development, delivery governance, and adoption-management skil

ls.· Working knowledge of AI platform dependencies, including cloud delivery, data readiness, governance approvals, security reviews, and production suppo

rt.Preferred experie

nce· Banking, financial services, fintech, risk, operations, compliance, customer service, banker productivity, or enterprise productivity backgrou

nd.· Experience delivering AI copilots, knowledge assistants, automation tools, analytics products, AI platforms, data products, or citizen-development progra

ms.· Familiarity with AIRP-style platform models, AWS-hosted AI platforms, Power Platform, Copilot Studio, Power Apps, Power Automate, Power BI, AI governance, model risk, data privacy, cybersecurity, and Responsible AI requireme

nts