Senior Product Manager – Controls & AI Transformation, Trusts & Estates, VP
Listed on JPMorganChase’s official careers site. Posted September 14, 2026. Check that it is still open and apply there.
Apply on JPMorganChase’s careers site →Job description
Role Summary
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.
Key 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.
Required Qualifications
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.
Preferred Qualifications
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).
Core Competencies
Controls mindset + innovation: balances speed with safety; designs “controls by default,” not bolted on later.
Strategic product leadership (IC)
creates clarity from ambiguity; sets direction and drives execution through others.
Stakeholder leadership
builds alignment across business, Technology, and second line partners; navigates conflict constructively.
AI transformation leadership
understands what it takes to productionize AI responsibly (governance, monitoring, adoption, and change). Success Measures (First 6–12 Months) Delivery of prioritized AI-enabled capabilities that reduce cycle time and rework in Trusts & Estates workflows. Demonstrable improvements in control effectiveness (e.g., better evidence capture, fewer exceptions, improved QA outcomes). Adoption metrics (active users, frequency, task completion) and measurable productivity/quality impact.
Strong governance posture
audit-ready documentation, clear approvals, and stable operational support model.
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