Director – AI Product Manager

ITSMF; St. Louis (MO); On-site; USD 173,000 - 294,000; Full time

Benefits offered by this job

Medical and prescription drug coverage

Dental coverage

Vision coverage

Disability insurance (short/long-term)

Job summary

ITSMF is seeking a Director of AI Product Management to own the strategy, roadmap, and outcomes of enterprise AI products and reusable AI capabilities across domains. You will lead discovery, prioritize features, and drive measurable value with cross-functional teams, ensuring AI solutions are scalable, explainable, and aligned with responsible AI practices.

The role requires strong AI product leadership, collaboration with engineering, data, architecture, risk, and business groups, and the

Qualifications

• Bachelor’s degree in computer science, engineering, product management or related field.
• 7+ years’ experience in product management incl translating business needs into technical requirements and leading product discovery and validation.
• 3+ years’ experience in AI/ML.
• Strong understanding of AI technologies and financial services.
• Product operating model methodologies, including AI driven PDLC.
• AI technologies and their applications in business contexts.
• Metrics and frameworks for tracking product AI model and agent success and impact.
• Responsible AI practices and regulatory compliance requirements.
• UX principles and their integration into product AI capability design.

Responsibilities

• Translate the firm’s vision and AI strategies into product strategy, value proposition, outcomes, priorities, roadmap, and investment recommendations for assigned AI products and capability domains.
• Own product strategy for assigned domains, translating enterprise priorities and customer needs into scalable requirements, evaluation criteria, and prioritized work.
• Lead continuous discovery and test hypotheses through research, prototypes, experiments, evaluations, proofs of concept, and pilots.
• Use customer evidence, product data, technical findings, and business measures to guide prioritization, investment, scaling, optimization, and retirement decisions.
• Own the full product lifecycle from discovery and launch through adoption, operation, modernization, and retirement, remaining accountable for customer value, business outcomes, reuse, product health, risk, and value realization.
• Define the end-to-end product experience, including customers, use cases, AI behavior, data and knowledge needs, integrations, human oversight, controls, monitoring, support, and service expectations.
• Create reusable AI products with clear boundaries, consumers, interfaces, dependencies, supported uses, limitations, ownership, and operating expectations.
• Contribute to and apply interoperable patterns across models, agents, skills, knowledge assets, workflows, platforms, and governance capabilities while balancing local needs with enterprise scale and standardization.
• Apply deep AI product expertise and technical fluency to challenge assumptions, evaluate alternatives, identify dependencies, and make informed tradeoffs with engineering, data, architecture, cybersecurity, experience, and business teams.
• Recognize and manage AI limitations and risks, including unreliable outputs, bias, data leakage, inappropriate actions, security threats, model drift, and workflow failure.
• Own the success measures, and be accountable for results, across customer value, business outcomes, adoption, reuse, quality, reliability, cost, operational performance, scalability, and risk.
• Lead cross-functional teams toward measurable outcomes and communicate product health, risks, assumptions, dependencies, tradeoffs, and lessons learned to senior leaders and stakeholders.
• Own the product roadmap and be accountable for delivery against measurable outcomes, escalating and aligning with senior leaders on investment, tradeoff, and dependency decisions.
• Define launch, integration, enablement, documentation, change, support, monitoring, and adoption strategies, and resolve barriers to effective operation and scale.
• Embed responsible AI, privacy, security, legal, regulatory, accessibility, records, and model-risk requirements throughout the product lifecycle, with clear intended uses, limitations, controls, oversight, and escalation paths.
• Serve as a trusted advisor, coach and mentor Product Managers on the team, and contribute to reusable frameworks, standards, evaluation practices, and customer-centered ways of working while adopting and applying them across owned domains.

Skills

AI product mgmt

Regulatory compliance

Financial services

PDLC

Education

Bachelor’s degree in CS/engineering/PM or related field

Master’s degree in AI/PM or related field

Job description

Position Schedule: Full-Time

This job posting is anticipated to remain open for 30 days, from 13-Nov-2026. The posting may close early due to the volume of applicants.

The Director, AI Product Manager is responsible for the strategy, roadmap, and outcomes of a defined set of enterprise AI products and reusable AI capabilities that serve multiple products, business domains, customer experiences, and enterprise workflows.
This role treats AI as the product, owning the strategy, discovery, prioritization, adoption, lifecycle management, and measurable outcomes of shared AI capabilities rather than discrete applications. Working in partnership with the Senior Director/Managing Director, who sets the vision for AI Product Management, the Director translates that vision into product strategy and roadmaps, drives discovery and prioritization, and is accountable for measurable value creation through scalable, reusable AI solutions.
The Director, AI Product Manager is accountable for one or more defined AI product or capability domains. Depending on organizational priorities, customer needs, and business strategy, these domains may focus on enabling AI creation and adoption, delivering AI-powered experiences, providing trusted information and intelligence, driving automation and decision support, or ensuring the governance, reliability, and operation of AI solutions.
Specific products and services within these domains may evolve over time and can include reusable AI capabilities such as models, agents, skills, functions, tools, knowledge, retrieval capabilities, builder experiences, low-code solutions, platform capabilities, governance services, observability capabilities, and other emerging AI technologies.
This role informs product and capability strategy across interconnected AI products, contributes to enterprise AI direction, and serves as a trusted advisor to business, technology, product, risk, and operational leaders. The Director works closely with colleagues across Engineering, Data, Product Management, Architecture, Experience, Risk, and Business areas to ensure AI capabilities deliver measurable customer and business value while remaining scalable, reusable, explainable, and aligned with responsible AI practices.
The role also strengthens AI Product Management capabilities within the Director’s team and across partner teams through product leadership, coaching, mentoring, collaboration, and the application of AI Product Management best practices.
The Director is expected to own product strategy, roadmaps, and outcomes for a capability domain, within the vision set by senior leadership, while ensuring the underlying products, services, and experiences are scalable, reusable, measurable, and aligned with enterprise objectives.

What You’ll Do

• Translate the firm’s vision and AI strategies into product strategy, value proposition, outcomes, priorities, roadmap, and investment recommendations for assigned AI products and capability domains.
• Own product strategy for assigned domains, translating enterprise priorities and customer needs into scalable requirements, evaluation criteria, and prioritized work.
• Lead continuous discovery and test hypotheses through research, prototypes, experiments, evaluations, proofs of concept, and pilots.
• Use customer evidence, product data, technical findings, and business measures to guide prioritization, investment, scaling, optimization, and retirement decisions.
• Own the full product lifecycle from discovery and launch through adoption, operation, modernization, and retirement, remaining accountable for customer value, business outcomes, reuse, product health, risk, and value realization.
• Define the end-to-end product experience, including customers, use cases, AI behavior, data and knowledge needs, integrations, human oversight, controls, monitoring, support, and service expectations.
• Create reusable AI products with clear boundaries, consumers, interfaces, dependencies, supported uses, limitations, ownership, and operating expectations.
• Contribute to and apply interoperable patterns across models, agents, skills, knowledge assets, workflows, platforms, and governance capabilities while balancing local needs with enterprise scale and standardization.
• Apply deep AI product expertise and technical fluency to challenge assumptions, evaluate alternatives, identify dependencies, and make informed tradeoffs with engineering, data, architecture, cybersecurity, experience, and business teams.
• Recognize and manage AI limitations and risks, including unreliable outputs, bias, data leakage, inappropriate actions, security threats, model drift, and workflow failure.
• Own the success measures, and be accountable for results, across customer value, business outcomes, adoption, reuse, quality, reliability, cost, operational performance, scalability, and risk.
• Lead cross-functional teams toward measurable outcomes and communicate product health, risks, assumptions, dependencies, tradeoffs, and lessons learned to senior leaders and stakeholders.
• Own the product roadmap and be accountable for delivery against measurable outcomes, escalating and aligning with senior leaders on investment, tradeoff, and dependency decisions.
• Define launch, integration, enablement, documentation, change, support, monitoring, and adoption strategies, and resolve barriers to effective operation and scale.
• Embed responsible AI, privacy, security, legal, regulatory, accessibility, records, and model-risk requirements throughout the product lifecycle, with clear intended uses, limitations, controls, oversight, and escalation paths.
• Serve as a trusted advisor, coach and mentor Product Managers on the team, and contribute to reusable frameworks, standards, evaluation practices, and customer-centered ways of working while adopting and applying them across owned domains.

Edward Jones’ compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account. Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm’s Employee Assistance Program. For more information on the Benefits available to Edward Jones associates, please visit our benefits page.

Hiring Minimum: $172800

Hiring Maximum: $294100

What you will need:

• Bachelor’s degree in computer science, engineering, product management or related field.
• 7+ years’ experience in product management includes translating business needs into technical requirements and leading product discovery and validation.
• 3+ years’ experience in AI/ML.
• Strong understanding of AI technologies and financial services.
• Product operating model methodologies, including AI driven PDLC.
• AI technologies and their applications in business contexts.
• Metrics and frameworks for tracking product AI model and agent success and impact.
• Responsible AI practices and regulatory compliance requirements.
• User experience (UX) principles and their integration into product AI capability design.

What you’ll need:

• Master’s Degree in Artificial Intelligence, Product Management, or a related field.
• 5+ years’ experience in AI product management, with a focus on responsible AI practices and regulatory compliance in a financial services context.
• Financial services industry practices and regulations.
• Emerging trends in AI product model and agent development and management.
• Data governance and integrity management.
• Risk management and compliance in AI product AI model and agent development.
• Advanced data visualization techniques for product insights.