
at J.P. Morgan
Bulge Bracket Investment BanksPosted 2 days ago
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**Product Manager - AI/ML Solutions**: Lead strategy for Databricks-based Model Experimentation Platform, ensuring scalable, secure AI/ML workflows in banking. 5+ years' experience, 3+ leading large-scale AI/ML Databricks platforms. Drive migrations, embed governance, and champion operational resilience.
- Compensation
- Not specified
- City
- New York City
- Country
- United States
Currency: Not specified
Full Job Description
Location: New York, NY, United States
As a Product Manager in Data and Analytics, you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. As a core leader, you are responsible for acting as the voice of the customer and developing profitable 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.
- Develops a product strategy and product vision that delivers value to customers
- Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap
- Owns, maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition
- Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability
- Drives the migration and integration of Databricks-based solutions, identifying dependencies, mitigating risks, and coordinating with cross-functional teams to ensure seamless execution.
- Collaborates with data science, engineering, architecture, and compliance teams to embed governance controls into product design and operations.
- Champions observability, monitoring, and operational resilience for AI/ML model experimentation workflows to ensure platform stability and reliability.
- Engages with internal customers and stakeholders to gather feedback, understand evolving needs, and translate them into actionable product enhancements.
- Leads vendor evaluation and selection processes related to model experimentation, ensuring alignment with strategic and compliance requirements.
- Communicates product vision, progress, and challenges transparently to senior leadership and critical partners, driving consensus and resource prioritization.
- Fosters a culture of innovation, continuous improvement, and collaboration across product, engineering, and architecture teams.
- 5+ years of experience or equivalent expertise in product management or a relevant domain area
3+ years leading product strategy and delivery for a large-scale Databricks-based AI/ML platform (e.g., model experimentation, MLflow, feature engineering, governance, and platform operations).
- Advanced knowledge of the product development life cycle, design, and data analytics
- Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management
- Deep expertise in AI/ML platform capabilities, specifically feature stores, model experimentation, and lifecycle management.
- Strong hands-on knowledge of Databricks and its ecosystem, including experience with platform migrations and integrations.
- Proven track record of delivering enterprise-grade AI/ML solutions in highly regulated environments.
- Demonstrated ability to lead cross-functional teams in matrixed organizations, managing dependencies and mitigating risks effectively.
- Excellent communication skills with the ability to influence senior leadership and diverse stakeholders.
- Strong strategic thinking and customer-centric mindset, with a focus on scalability, security, and operational excellence.
Experience with observability, monitoring, and governance frameworks for AI/ML workloads.
- Demonstrated prior experience working in a highly matrixed, complex organization
- Prior experience in financial services or similarly regulated industries.
- Knowledge of compliance frameworks related to AI/ML and data security.
- Strong understanding of market trends and emerging technologies in AI/ML infrastructure.




