Applied AI/LLM Lead Product Manager - Vice President
Jpmc Cx_1001 · London, United Kingdom
Join us to help shape how the world's largest bank uses AI and autonomous agents. You will have the opportunity to own a portfolio of innovative products that solve mission-critical problems and directly impact daily work for bankers. We value innovation, accountability, and continuous improvement, offering you real influence over how agentic AI is built, governed, and adopted across the firm. As part of our team, you will collaborate with talented engineers, data scientists, and business partners to deliver solutions at scale. Your leadership will drive the future of AI and agentic systems within a dynamic, supportive environment.
As a Senior Product Manager – Agentic AI Portfolio in the AI & Agentic Systems team, you will own the strategy, roadmap, and production performance of a portfolio of agentic solutions. You will work with senior business, technology, and controls stakeholders to identify high-value opportunities and turn them into reliable, scalable AI workflows that meet our standards for performance, safety, and compliance. You will set the standard for agent design, evaluation, and production, building reusable patterns and infrastructure to accelerate delivery. Your role will influence how agentic AI is adopted and governed across the firm, ensuring alignment with data governance and control standards.
Job Responsibilities:
- Own the product strategy, vision, and multi-year roadmap for agentic AI products, aligning priorities with business objectives and firmwide AI strategy
- Lead cross-functional delivery pods across Engineering, Data Science, Design, and Controls, driving outcomes from discovery through production
- Define and govern agent behavior, autonomy boundaries, human-in-the-loop controls, and escalation paths
- Set evaluation standards and frameworks for agentic systems, including offline and online evaluations, red-teaming, regression testing, and production monitoring
- Shape the architecture of agents and supporting infrastructure, advocating for reusable components and shared platform capabilities
- Prioritize investment across the portfolio using business value, risk, technical feasibility, and reuse potential
- Collaborate with senior business stakeholders to identify and size opportunities for AI-driven efficiency, risk reduction, or revenue growth
- Define portfolio-level success metrics covering reliability, adoption, reuse, and business impact, and report progress to senior leadership
- Build structured user feedback loops and translate insights into product enhancements and roadmap decisions
- Ensure alignment with data governance, model risk management, compliance, and control standards, serving as the product point of contact for Controls and Risk partners
- Influence across a matrixed organization to remove blockers, align dependencies, and drive adoption at scale
- Mentor and elevate product practices across the AI & Agentic Systems team
Required Qualifications, Capabilities, and Skills:
- Significant experience in product management, data products, or technology delivery, including ownership of multiple products or a product portfolio
- Proven track record of shipping LLM-powered, autonomous, or agentic AI products to production and managing them at scale
- Expertise in designing evaluation frameworks for agentic systems, including reasoning about probabilistic behavior, failure modes, drift, and reliability tradeoffs
- Strong command of the AI/ML lifecycle, including training, fine-tuning, validation, deployment, monitoring, and iteration
- Sound judgment on production data, including pipeline stability, data quality, and the impact of quality issues on agentic workflows
- Technical fluency in system architecture, APIs, tool and agent orchestration, and data pipelines
- Experience leading cross-functional pods to deliver complex, high-impact programs
- Executive-level communication and stakeholder management skills, with the ability to influence senior leaders and explain complex AI concepts to non-technical audiences
- Experience operating within a large, regulated institution, including collaboration with governance, model risk, and control functions
- Ability to set product strategy, make portfolio-level prioritization decisions, and deliver measurable business outcomes
Preferred Qualifications, Capabilities, and Skills:
- Experience in commercial and investment banking or financial services
- Experience building net-new AI infrastructure or shared agentic platforms used across multiple products
- Track record of driving reuse and standardization of agentic components across teams
- Demonstrated business impact from AI solutions, with quantified results in efficiency, revenue, or risk reduction
- Deep knowledge of data governance, model risk management, and regulatory expectations for AI in financial services
- Experience building feedback-driven product cultures and iterative improvement processes at scale
- Experience reporting portfolio performance, adoption, and ROI to senior leadership