Senior Product Manager (Individual Contributor) – Controls & AI Transformation, Trusts & Estates

JPMorgan Chase & Co.•New York, NY

10d

About The Position

We are seeking an experienced Product Manager with a strong Controls background to lead AI-enabled product transformation within the Trusts & Estates business. This is an individual contributor (IC) role—who brings awareness to and manages risk in the business. This individual will own product strategy and end-to-end delivery while partnering closely with Controls, Legal/Compliance, Operations, Technology, Data/AI teams, and senior business stakeholders. The successful candidate will modernize and transform Trusts and Estates Controls while embedding robust governance, auditability, and risk management by design.

Requirements

8+ years of product management experience (or equivalent experience owning complex platforms/workflows end-to-end).
Demonstrated experience in a controls-heavy banking environment (e.g., Risk & Controls, Compliance, Audit, Operational Risk, governance, QA).
Proven track record delivering AI/automation/analytics products in production (not just pilots), with measurable business impact.
Strong knowledge of regulated process design: documentation standards, audit readiness, approvals, and evidence capture.
Exceptional stakeholder management and executive communication; ability to influence without authority.
Strong analytical and strategic skills: value sizing, prioritization frameworks, KPI/OKR design, and data-driven decisioning.

Nice To Haves

Experience in wealth management, private banking, fiduciary, trust administration, or estates domains.
Experience with operating model design (intake-to-scale, control gates, support model, training).

Responsibilities

Set product vision and strategy for AI transformation in Trusts & Estates Controls.
Own the roadmap and prioritization, translating business goals, regulatory obligations, and risk appetite into sequenced delivery plans (12–24 months) with clear outcomes and KPIs.
Lead discovery and define requirements: customer/user journeys, problem statements, use-case intake, value sizing, control impact assessment, and success metrics.
Embed controls into product design: governance workflows, approvals, audit trails, evidence capture, access controls, data handling requirements, and change management readiness.
Partner with engineering and data teams to deliver scalable, secure, and observable AI capabilities (e.g., retrieval/search over approved content, workflow automation, decision-support, quality checks).
Drive stakeholder alignment and decision-making across business, Controls, Compliance, Legal, Risk, Operations, and Technology; manage trade-offs transparently.
Own delivery execution using agile product practices: epics/user stories, acceptance criteria, release planning, dependency/risk management, and post-release measurement.
Champion responsible AI adoption: monitoring/feedback loops, human-in-the-loop controls where needed, and clear user guidance to reduce operational and conduct risk.
Enable adoption and change: training, communications, support readiness, and continuous improvement based on usage and control outcomes.