At JPMorganChase, we understand that customers seek exceptional value and a seamless experience from a trusted financial institution. That's why we launched Chase UK to transform digital banking with intuitive and enjoyable customer journeys. With a strong foundation of trust established by millions of customers in the US, we have been rapidly expanding our presence in the UK and soon across Europe. We have been building the bank of the future from the ground up, offering you the chance to join us and make a significant impact.

As a Product Manager within the International Consumer Bank at JPMorganChase, you will lead the product function for AI Engineering (AIE), reporting into the engineering lead and collaborating to set strategy and direction. AIE comprises two sub-teams: a platform team that builds the AI and MLOps capabilities developers across ICB use to take models and agents from experiment to production, and a team that builds internal AI agents and assistants that automate friction in how ICB operates. As Product Manager, you will own the product roadmap across both, operating with a high degree of autonomy, and work in close partnership with wider Engineering org to ensure the two teams' work compounds rather than diverges. You will translate complex, ambiguous needs into a clear, prioritized roadmap of capabilities that make AI delivery repeatable, compliant, and fast.

Job responsibilities

Partner with the engineering lead to set the AIE product vision and multi-year strategy, aligned to ICB and firmwide objectives, and own the product roadmaps that translate it into measurable outcomes across both AIE sub-teams.
Ensure the platform roadmap and the internal AI applications roadmap stay aligned, so that capabilities built by the platform team are validated and consumed by the applications team, and the applications team's needs inform platform priorities.
Author clear, detailed product requirements documents (PRDs) and own the backlog in Jira in close collaboration with engineering leads, decomposing initiatives into well-defined stories with crisp acceptance criteria, maintaining priority, and making data-informed trade-offs across scope, schedule, and risk.
Lead discovery with platform users and partners across ICB to define capabilities that improve developer experience, reliability, time to production, and compliance.
Partner with delivery leads to ensure architectures are scalable, reliable, and operationally sound, and that capabilities ship with evaluation, observability, and clear ownership.
Embed technology controls and regulatory requirements into product design, so that teams meet their obligations by adopting platform tooling rather than rebuilding controls bespoke.
Drive adoption of platform capabilities through clear documentation, enablement, and internal go-to-market, demonstrating measurable value to use case teams.
Define and track product KPIs across AIE, and use insights for continuous improvement.
Coordinate cross-team dependencies, remove impediments, and align stakeholders; resolve competing priorities with clear, evidence-based communication.
Establish high standards for product artifacts and decision quality, and work with Engineering peers to raise velocity and impact.

Required qualifications, capabilities & skills

Senior product management experience for technical platform or infrastructure products, delivering complex roadmaps in regulated environments with minimal oversight.
Strong understanding of the machine learning lifecycle and what it takes to move models and AI applications from experiment to production.
Outstanding stakeholder management and influence; builds trust through transparency and effective use of data; adept at resolving ambiguity and competing priorities.
Deep partnership with Engineering; fluent in discussing technical trade-offs with both technical and non-technical stakeholders.
Strong analytical and decision-making skills; comfortable using metrics and telemetry to guide priorities and measure outcomes.
Robust risk and controls mindset; integrates regulatory and technology control requirements into product strategy and execution.
Excellent written and verbal communication skills in English.
Bias to action; executes with urgency, discipline, and quality.

Preferred qualifications, capabilities & skills

Product management experience for AI/ML, MLOps, or data platforms.
Familiarity with MLOps concepts and frameworks, such as MLflow, Amazon SageMaker, and feature stores.
Familiarity with AI concepts, such as Retrieval-Augmented Generation (RAG), agentic system architectures, evaluation of LLMs and agents, and Model Context Protocol (MCP).
Hands-on experience with or solid understanding of Amazon Web Services (AWS).
Understanding of cloud architecture and the software development lifecycle.
Experience coaching and mentoring other product managers and setting a high bar for execution.
Experience operating at scale in highly available, secure environments.

#ICBEngineering #ICBCareers

Job responsibilities

Partner with the engineering lead to set the AIE product vision and multi-year strategy, aligned to ICB and firmwide objectives, and own the product roadmaps that translate it into measurable outcomes across both AIE sub-teams.
Ensure the platform roadmap and the internal AI applications roadmap stay aligned, so that capabilities built by the platform team are validated and consumed by the applications team, and the applications team's needs inform platform priorities.
Author clear, detailed product requirements documents (PRDs) and own the backlog in Jira in close collaboration with engineering leads, decomposing initiatives into well-defined stories with crisp acceptance criteria, maintaining priority, and making data-informed trade-offs across scope, schedule, and risk.
Lead discovery with platform users and partners across ICB to define capabilities that improve developer experience, reliability, time to production, and compliance.
Partner with delivery leads to ensure architectures are scalable, reliable, and operationally sound, and that capabilities ship with evaluation, observability, and clear ownership.
Embed technology controls and regulatory requirements into product design, so that teams meet their obligations by adopting platform tooling rather than rebuilding controls bespoke.
Drive adoption of platform capabilities through clear documentation, enablement, and internal go-to-market, demonstrating measurable value to use case teams.
Define and track product KPIs across AIE, and use insights for continuous improvement.
Coordinate cross-team dependencies, remove impediments, and align stakeholders; resolve competing priorities with clear, evidence-based communication.
Establish high standards for product artifacts and decision quality, and work with Engineering peers to raise velocity and impact.

Required qualifications, capabilities & skills

Senior product management experience for technical platform or infrastructure products, delivering complex roadmaps in regulated environments with minimal oversight.
Strong understanding of the machine learning lifecycle and what it takes to move models and AI applications from experiment to production.
Outstanding stakeholder management and influence; builds trust through transparency and effective use of data; adept at resolving ambiguity and competing priorities.
Deep partnership with Engineering; fluent in discussing technical trade-offs with both technical and non-technical stakeholders.
Strong analytical and decision-making skills; comfortable using metrics and telemetry to guide priorities and measure outcomes.
Robust risk and controls mindset; integrates regulatory and technology control requirements into product strategy and execution.
Excellent written and verbal communication skills in English.
Bias to action; executes with urgency, discipline, and quality.

Preferred qualifications, capabilities & skills

Product management experience for AI/ML, MLOps, or data platforms.
Familiarity with MLOps concepts and frameworks, such as MLflow, Amazon SageMaker, and feature stores.
Familiarity with AI concepts, such as Retrieval-Augmented Generation (RAG), agentic system architectures, evaluation of LLMs and agents, and Model Context Protocol (MCP).
Hands-on experience with or solid understanding of Amazon Web Services (AWS).
Understanding of cloud architecture and the software development lifecycle.
Experience coaching and mentoring other product managers and setting a high bar for execution.
Experience operating at scale in highly available, secure environments.

#ICBEngineering #ICBCareers