Jobs
Required skills
Machine Learning
You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients.
As a Data and AI Product Manager focusing on Knowledge Management, you are an integral part of the Chief Data & Analytics Office that innovates new solutions for the firm's AI use cases. You will build platform products to leverage the firm's incredibly rich proprietary data assets and enable RAG, while collaborating with product leaders, data scientists and engineers across lines of businesses. As a core leader, you are responsible for acting as the voice of the customer and developing products that provide customer value. Utilizing your deep understanding of how to get a product off the ground, you guide the successful launch of products, gather crucial feedback, and ensure top-tier client experiences. With a strong commitment to scalability, resiliency, and stability, you collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations.
Job responsibilities
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Drive the product vision and strategy of enterprise Knowledge Management, enabling RAG and agentic workflows across unstructured data
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Partner closely with all lines of business to identify, prioritize and solution key AI and data use cases
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Drive the end-to-end product management lifecycle, including integration of data sources – from requirements gathering, prioritization, solutioning, writing clear PRDs and partnering with designers and engineers on execution
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Own, maintain, and develop a product backlog to support the overall strategic roadmap and value proposition
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Work with client engagement and product marketing teams to refine product positioning and messaging
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Draft communication materials for stakeholder discussions at varying levels of seniority and technicality
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Stay at the forefront of what’s possible with AI and RAG, especially industry developments
Required qualifications, capabilities, and skills
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5+ years of experience or equivalent expertise in AI and data platform product management or a relevant domain area
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Advanced knowledge of the product development lifecycle, design, and data analytics
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Track record of leading product management lifecycle activities including discovery, ideation, strategic development, requirements definition, and value management
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Strong ability to communicate complex technical materials to technical and non-technical stakeholders, in both written and verbal forms
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Excellent ability to collaborate with senior stakeholders and technical leads
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Organized with a great sense of ownership and accountability
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Bachelor’s or Master’s degree in Machine Learning or Computer Science
Preferred qualifications, capabilities, and skills
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Demonstrated prior experience working in a highly matrixed, complex organization
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Technical expertise in retrieval-augmented generation and advanced RAG, such as GraphRAG and search
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Prior engineering experience, with skills in Python programming and SQL
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
Employees
New York City
Headquarters
$500B
Valuation
Reviews
3.8
10 reviews
Work-life balance
3.5
Compensation
4.0
Culture
3.8
Career
3.2
Management
2.8
68%
Recommend to a friend
Pros
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
Cons
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
Salary Ranges
44 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analytics Solutions Associate
1 reports
$139,000
total per year
Base
$107,000
Stock
-
Bonus
-
$139,000
$139,000
Interview experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 75%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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