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JP Morgan Chase

Runs a consumer bank and an investment bank

Artificial Intelligence/Machine Learning Product Delivery Manager - Payments, Vice President

Technical Product ManagementConfirmed live in the last 24 hours
Full-time$133k - $200kIn-person

About the Job

Requirements

  • Experience in product management or an equivalent role delivering data- or AI-enabled products from concept to launch.
  • Deep understanding of machine learning models, especially anomaly detection techniques and operationalization, including monitoring, drift, retraining strategy, and alert quality.
  • Hands-on fluency with Python and SQL to partner effectively, prototype, validate datasets and outputs, and reason about implementation.
  • Strong understanding of large language models, including retrieval-augmented generation, prompt and context design, evaluation approaches, and common failure modes.
  • Familiarity with agentic artificial intelligence systems, including tool-using agents, orchestration patterns, guardrails, and human-in-the-loop designs.
  • Ability to work with structured and semi-structured data and define data requirements for machine learning and large language model systems, including quality, lineage, and access patterns.
  • Strong stakeholder management skills in complex environments, with the ability to drive decisions, tradeoffs, and execution.
  • At least 5 years of experience or equivalent expertise in product delivery or a relevant domain area.
  • Demonstrated ability to execute operational management and change readiness activities.
  • Strong understanding of delivery and a proven track record of implementing continuous improvement processes.
  • Experience in product- or platform-wide release management, including deployment processes and strategies.
  • Experience deploying containerized AI/ML or automation applications on AWS using ECS with Fargate or EC2 launch type, and familiarity with related services including ECR, ALB, CloudWatch, and IAM roles for task execution.
  • Proficient knowledge of the product development life cycle, design, and data analytics.

Responsibilities

  • Own the AI automation roadmap for the payments platform, focused on measurable outcomes such as reduced exceptions, faster triage, fewer breaks, improved straight-through processing, and improved detection and precision.
  • Identify and prioritize high-impact payment workflows suitable for AI augmentation or automation, including investigation, reconciliation support, exception classification, root-cause suggestions, and alert deduplication.
  • Lead rapid proof-of-concept development using AI/ML to validate value quickly, then scale successful proofs of concept into production-grade capabilities.
  • Drive anomaly detection strategy, including signals, feature sets, model approach, thresholds, and monitoring, to detect payment issues, operational anomalies as applicable, and process breaks early.
  • Translate business and user needs into clear product requirements, user stories, acceptance criteria, and phased delivery plans.
  • Partner with engineering and machine learning teams to design large language model and retrieval-augmented generation solutions, including knowledge grounding, context retrieval, evaluation, safety and controls, and feedback loops.
  • Define and track success metrics, including anomaly precision and recall, false positives, latency, automation rate, operational savings, reliability, and control posture.
  • Drive alignment across operations, technology, data, and risk and controls stakeholders, and own end-to-end delivery from discovery to launch and iteration.
  • Lead end-to-end product delivery processes, including intake, dependency management, release management, product operationalization, delivery feasibility decisions, and product performance reporting, while escalating opportunities to improve efficiencies and functional coordination.
  • Lead change management activities across functional partners and ensure adherence to the firm's risk, controls, compliance, and regulatory requirements.
  • Manage timelines and dependencies, monitor blockers, ensure adequate resourcing, and liaise with stakeholders and functional partners.

Desired Qualifications

  • Payments industry knowledge, including payment flows, exceptions, investigations, reconciliation, messaging and clearing concepts, and operational risk.
  • Experience productizing machine learning in regulated environments, including model risk, controls, explainability, auditability, and reliability.
  • Experience building or leading evaluation frameworks, including offline tests, golden datasets, human review, and online monitoring.
  • Prior work delivering automation in high-scale operational platforms, including workflow orchestration, case management, and alerting systems.

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1799

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