Digital Product Manager (Client + Advisor Platforms, AI-enabled) - VP

JPMorganChase•Jersey City, NJ

About The Position

PB Digital is seeking a VP, Digital Product Manager to lead strategy and delivery of client- and advisor-facing digital platforms for the Private Bank. This role is for a strong product leader who can take ideas from discovery to scaled delivery, and who can translate AI/ML capabilities into compliant, measurable outcomes that improve client experience and advisor productivity.

Requirements

6+ years of digital product management experience with demonstrated ownership of roadmaps and outcomes.
Experience shipping or scaling products that incorporate AI/ML (including GenAI), with an understanding of data readiness, evaluation, monitoring, and human-in-the-loop controls.
Strong execution skills: prioritization, backlog management, release planning, and cross-team dependency management.
Excellent written and verbal communication; ability to influence across senior stakeholders and matrixed teams.
Customer-first mindset with strong UX instincts (for both client and advisor journeys)
Structured prioritization and data-driven decisioning
Technical fluency with AI-enabled product delivery
Risk-aware product thinking in a regulated environment
Ownership mindset and collaborative leadership

Nice To Haves

Experience delivering products in wealth management, private banking, or other regulated financial services.
Onboarding / KYC / account opening product experience.
Familiarity with experimentation, analytics instrumentation, and product telemetry.
Experience with APIs, platform modernization, and workflow digitization.

Responsibilities

Own product vision, multi-quarter roadmap, and OKRs across client and advisor digital experiences.
Identify and prioritize opportunities across onboarding, servicing, insights, personalization, and digital engagement.
Define AI use cases and requirements (e.g., intelligent workflows, personalization, summarization, next-best-actions) and partner with AI/ML, data, and engineering teams to deliver.
Establish success metrics and monitoring approaches for AI features, including quality, performance, and user impact.
Lead the full product lifecycle: discovery, requirements, MVP definition, delivery, launch, experimentation, and iteration.
Write crisp epics/features, define acceptance criteria, manage dependencies, and drive delivery across multiple teams.
Partner with Design, Engineering, Data, Operations, Legal, Risk, Compliance, Controls, and Cyber to deliver secure, resilient experiences.
Align stakeholders, communicate tradeoffs, and drive decisions with senior partners.
Ground decisions in user research and journey mapping; ensure solutions are intuitive, accessible, and measurable.
Define and track success metrics (adoption, engagement, task completion, cycle time reduction, defect rates, satisfaction measures).
Ensure features meet privacy, data handling, recordkeeping, model governance, and audit requirements.
Drive release readiness (training, communications, support model, incident/defect triage, telemetry).