Role Summary

The AI Product Manager will lead some of Global Distribution’s most consequential AI-enabled transformations, beginning with fundamental questions about how client experiences, commercial activities, and business workflows should operate in an AI-native world and carrying those ideas through to measurable business outcomes.

Reporting directly to the Head of Global Distribution AI Strategy & Transformation, this role will own one or more high-conviction transformation opportunities that require dedicated incubation and sustained cross-functional leadership. These initiatives may span business processes, client experiences, data, technology, roles, controls, and ways of working and will often develop over multiple quarters.

The AI Product Manager is expected to begin with the future state rather than the existing process: if this experience or workflow were being designed from scratch today, knowing what artificial intelligence can now make possible, how should it work?

From there, the role is accountable for turning that ambition into reality—building conviction around the vision, defining the business case and product strategy, sequencing a practical roadmap, making difficult product and design decisions, partnering with Technology and Data through delivery, driving organizational change, and demonstrating realized business value.

This is not a traditional backlog-management role. The AI Product Manager is a senior transformation leader who combines strategic imagination, product judgment, business acumen, AI fluency, and execution discipline to create materially different ways of working.

Responsibilities

Reimagine the Future:

• Start with the business or client problem and develop a bold, coherent point of view on how the experience or workflow should operate as AI capabilities continue to advance.
• Challenge assumptions embedded in existing processes, technology limitations, roles, handoffs, and operating models rather than simply automating the current state.
• Develop a deep understanding of client needs, Associate workflows, business economics, data, technology, risk, and competitive dynamics relevant to the opportunity.
• Translate emerging AI capabilities into practical strategic possibilities, identifying where AI can fundamentally change the experience rather than merely make existing activities faster.
• Create clarity around what should remain distinctly human, what should be AI-enabled, what can be automated, and what work may no longer need to exist.

Turn the Vision into a Product Strategy:

• Define the product vision, target-state experience or workflow, value proposition, business case, success measures, and strategic roadmap required to bring the transformation to life.
• Break a large future-state ambition into a sequence of valuable releases and decisions that create momentum while preserving the long-term vision.
• Establish clear product priorities and make deliberate trade-offs across business value, client experience, speed, scope, data, technology, risk, cost, and organizational readiness.
• Translate ambiguous business needs into sufficiently clear product requirements, design principles, workflows, and decisions for Technology, Data, Design, Risk, and other delivery partners.
• Continuously evolve the roadmap as AI capabilities, user needs, technical feasibility, and organizational learning change.

Lead End-to-End Delivery:

• Maintain end-to-end accountability for the transformation from early concept through design, engineering delivery, launch, adoption, and ongoing evolution.
• Serve as the primary connection across business leaders, Technology, Data, Design, Risk, Legal, Compliance, and other enterprise partners required to deliver the product.
• Engage credibly in architecture, data, build-vs.-buy, integration, model, and design discussions and ensure technical decisions preserve the intended business outcome and sufficient flexibility for future evolution.
• Drive timely resolution of blockers, dependencies, competing priorities, and difficult trade-offs across a complex matrixed organization.
• Preserve clarity of objectives and accountability through delivery handoffs; ensure that technical completion is not mistaken for successful delivery when the intended business outcome has not been achieved.
• Maintain urgency and momentum without sacrificing the quality, controls, or enterprise readiness required for durable solutions.

Make the Transformation Real:

• Build strong business sponsorship and engage the Associates, managers, and leaders whose work or client experience will change as a result of the product.
• Partner with change, learning, and business teams to redesign roles, processes, procedures, incentives, controls, and ways of working required to capture the full value of the product.
• Own the business case and expected value outcomes for the transformation, including appropriate measures of client impact, commercial outcomes, productivity, capacity, quality, cost, adoption, or other relevant results.
• Partner with the AI Portfolio, Governance & Value Realization team to establish consistent measurement while retaining direct accountability for whether the product delivers its expected value.
• Use evidence from adoption and realized outcomes to improve the product, change course when required, and make recommendations to scale, accelerate, rethink, or stop investments.
• Capture broader lessons and reusable capabilities that can inform other AI products, targeted workflow transformations, and the broader GD AI ecosystem.

Mindset

• Starts with the blank sheet of paper. Naturally asks how the business should work in the future rather than accepting the current state as the starting constraint.
• Strategic and imaginative. Can connect emerging AI capabilities with client needs, business strategy, workflows, and operating-model possibilities others may not immediately see.
• Makes ideas real. Enjoys the hard work of translating an ambitious vision into decisions, roadmaps, products, organizational change, and measurable outcomes.
• Intellectually curious. Quickly develops depth across unfamiliar business, technology, data, and AI topics and asks incisive questions of experts.
• High ownership. Does not stop at a recommendation, specification, engineering handoff, or launch; remains accountable for the business outcome.
• Comfortable in ambiguity. Creates clarity and forward motion without waiting for perfect information.
• AI-forward. Actively experiments with and learns from rapidly evolving AI capabilities so that the vision of what is possible continues to expand.
• Influential without relying on authority. Builds conviction, challenges constructively, and aligns senior stakeholders across a complex matrix.
• Low ego and team-oriented. Seeks the best answer rather than personal ownership of the answer and builds strong partnerships with business and technical teams.

Qualifications

Required:

• Bachelor’s degree or equivalent experience in business, technology, engineering, economics, design, or a related discipline; advanced degree preferred and 8+ years of related experience
• Experience across product management, strategy, business transformation, management consulting, digital transformation, innovation, or related roles.
• Demonstrated experience taking ambiguous, strategically important problems from initial concept through implementation and measurable business outcomes.
• Proven ability to develop compelling product visions and translate them into actionable roadmaps, priorities, requirements, and delivery decisions.
• Experience leading complex cross-functional initiatives spanning business, technology, data, and organizational change.
• Strong business judgment and ability to develop business cases, identify value drivers, and make difficult investment and prioritization trade-offs.
• Strong understanding of generative AI, large language models, agentic workflows, and emerging AI-enabled business models and experiences.
• Sufficient technical fluency to engage credibly with engineers, architects, data leaders, and AI specialists on architecture and implementation trade-offs.
• Exceptional written and verbal communication skills and demonstrated ability to influence senior leaders.

Preferred:

• Experience in asset management, financial services, distribution, sales, marketing, client service, or another complex client-facing environment.
• Experience building AI-enabled products or transforming workflows using generative AI in a complex enterprise setting.
• Experience owning the full product lifecycle from vision and incubation through production, adoption, and ongoing optimization.
• Familiarity with enterprise architecture, data governance, privacy, responsible AI, risk management, and regulated product-development environments.
• Track record of delivering measurable improvements in client experience, revenue or commercial outcomes, productivity, capacity, quality, or cost.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to one day per week from home.

Base Salary Ranges

Please review the job posting for the location of this specific opportunity.

Placement within the range provided above is based on the individual’s relevant experience and skills for the role.  Base salary is only one component of our total compensation package.  Employees may be eligible for a discretionary bonus, which is determined upon company and individual performance.

Benefits