AI Product Director

Overview

As Applied AI Product Director at JPMorganChase within J.P. Morgan Personal Investing, you own the AI product vision, strategy, and roadmap across large language models and agentic systems. You lead cross-functional teams to move AI solutions from concept to production at scale, balancing build, buy, and partner decisions. You shape AI integration strategies, establish guardrails, and govern risk while delivering measurable outcomes. You thrive in fast-paced, ambiguous environments and translate technical capabilities into practical, value-added tools for diverse stakeholders. This role offers the opportunity to influence how AI transforms customer experiences and product features at scale.

Responsibilities

• Develop and articulate a clear Applied AI product strategy and roadmap covering LLMs, agentic capabilities, AI assistants, intelligent automation, and rapid prototyping.
• Lead cross-functional teams to move AI solutions from concept to production at scale and decide on AI tooling and capabilities.
• Convert ambiguous demand into prioritized, validated AI use cases with measurable experiments and production pathways.
• Identify opportunities for autonomous agents and emerging integration standards to create step-change value while managing governance and dependencies.
• Enable teams to safely leverage AI tools through repeatable workflows, guardrails, and training, and resource AI use-case requests across functions.
• Work with data teams to surface insights, shape AI-ready datasets, and unlock features via NLP and LLMs.
• Deploy LLM and agentic capabilities to improve engineering quality, delivery speed, and resilience, including code review and incident analysis.
• Leverage internal AI platforms and prototyping infrastructure to move from idea to prototype and to production-grade solutions.
• Lead change impact assessments, own AI risk assessments, and contribute to risk appetite governance for applied AI.

Key requirements

• Extensive product management experience delivering AI/ML-powered products or platforms in financial services or tech, with cross-functional collaboration across Data Science, Platform Engineering, Model Risk, and governance bodies.
• Deep working knowledge of GenAI/LLMs, agentic systems, RAG architecture, and AI-assisted software development, translating AI capabilities into tools for non-technical users.
• Track record of owning AI product vision and delivering enterprise-scale AI/ML solutions with measurable outcomes.
• Strong understanding of AI/ML lifecycle management, deployment, monitoring, and governance.
• Hands-on, credible partner for engineering and data science; capable of API design, system architecture, and evaluating trade-offs.
• Experience identifying, validating, and prioritizing AI use cases through experiments in fast-paced environments.
• Experience building self-serve AI enablement programs with training, guardrails, templates, and adoption metrics.
• Understanding of AI regulatory and governance landscape, including responsible AI and model risk management.
• Excellent cross-functional communication, able to translate AI concepts for technical and non-technical audiences.

• Cross-functional collaboration
• Strategic thinking
• Adaptability
• GenAI/LLMs
• agentic systems
• RAG architecture

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