Financial Services - Technology Consulting - Product Manager - Senior

EY is a global professional services firm with a dedicated Financial Services Organization (FSO) that serves clients across banking, wealth and asset management, insurance, and real estate, hospitality and construction. The role focuses on product management within EY’s Product and Experience Design team, using AI-enabled and human-centered methods to help clients define strategies, develop requirements, prioritize backlogs, and deliver products and platforms in complex financial services environments.

Responsibilities:

• The goal is to support our clients in transforming their businesses through product management
• As a Product Manager, you will work with multidisciplinary feature teams, including user experience experts, architects, engineers, data and AI specialists and others, to define and launch products and services for large global organizations
• You will use user-centered, data-driven and AI-enabled methods to synthesize research, identify unmet needs, develop and test concepts, define business requirements and support product decisions
• You will advocate for users throughout the product lifecycle and apply human judgment to validate AI-generated insights and outputs
• You can simplify complex processes and touchpoints, prioritize opportunities, contribute to product roadmaps, manage product backlogs and coordinate teams to release quality products within planned timelines
• You understand modern platform structures, cloud architectures, digital platforms and enablers, data strategy considerations, and the opportunities and limitations of AI-enabled products
• In addition, you understand how product and delivery organizations operate within complex, regulated national and global companies
• Outside client engagements, you have experience supporting business development activities, such as pursuits and proposals, and practice-building activities such as mentoring colleagues and developing or delivering training
• • Support the development of product strategies that align with business objectives, identify appropriate opportunities for AI-enabled capabilities, and account for technology, data, experience design, risk and adoption considerations
• • Support the definition of product organization and operating models, including product taxonomy, organizational structure, funding methods, product delivery processes, governance models and decision rights, while considering the roles, skills, controls and human oversight needed for AI-enabled product development
• • Improve portfolio management with product metrics and OKRs that align work to business objectives and increase transparency/traceability of outcomes
• • Support technology delivery by using traditional and AI-enabled research and requirements tools to translate product vision, customer insights, business rules and enterprise knowledge into traceable business requirements, user stories and acceptance criteria; validate generated outputs with subject-matter experts; and help prioritize backlogs and maintain roadmaps
• • Support cross-functional teams of designers, engineers, data and AI specialists and testers through the software development lifecycle, using rapid prototypes and AI-assisted tools to test concepts, workflows and value hypotheses before implementation and deployment
• • Advocate for and help operationalize cross-functional practices such as user testing, experimentation, functional and regression test automation, evaluation of AI-enabled features, and alignment with industry, client, risk and regulatory standards
• • Use traditional and AI-enabled product management tools, such as JIRA, Azure DevOps, Aha!, Productboard, requirements repositories, AI assistants, enterprise knowledge tools and prototype-driven development platforms, to support discovery, prioritize opportunities, develop requirements, test concepts and deliver technology solutions
• • Use product analytics software and frameworks, such as Pendo and Amplitude, together with AI-enabled analysis, to synthesize user feedback, research, behavioral data and product performance; identify patterns and unmet needs; and translate findings into testable hypotheses and actionable recommendations
• • Advise on and implement best practices and standards for experience design, agile delivery, technology, data and responsible AI, adapting methods to client needs and established governance
• • Apply AI-enabled methods across selected parts of the product lifecycle—including research synthesis, concept generation, rapid prototyping, requirements development, backlog refinement and product analytics—to improve speed and quality. Use approved tools and reusable prompts, validate outputs and follow established safeguards for responsible use
• • Construct and communicate a compelling story to rally the client around potential changes and associated benefits
• • Drive desired outcomes defined in client engagements and carry through to implementation
• • Begin developing long-term client relationships and networks and cultivate business development opportunities
• • Effectively work with client engagement teams with diverse skills and backgrounds fostering an innovative and inclusive work environment
• • Demonstrate an understanding of the current technology and AI environment, relevant financial services trends and the evolving product management toolchain, and apply that understanding to engagement delivery and client service issues

Requirements:

• • Bachelor's degree in Computer Science, Engineering, Information Systems Management, or a related field and 3 years of progressive, post-baccalaureate work experience. Alternatively, will accept a Master's degree in Computer Science, Engineering, Information Systems Management, or a related field and 2 years of work experience
• • Experience using AI-enabled tools or methods to support one or more product activities—such as research synthesis, opportunity assessment, requirements development, rapid prototyping or product analytics—with appropriate human review of generated outputs
• • Proven delivery skills including the ability to identify issues and risks and escalate appropriately, manage communications with EY and client team members, and be accountable for client deliverables
• • Facilitate discussions with technical, design and business subject-matter resources to document requirements, establish a vision, and articulate alternatives for future state solutions across various domains and channels
• • Has supported product vision, defined and managed product roadmaps, prioritized and managed backlogs, and supported product or technology launches. Experience should include contributing to the identification of suitable AI-enabled opportunities, testing value or feasibility through prototypes or experiments, and defining measurable outcomes for AI-enabled features
• • Can participate in and drive ideation sessions, standups, sprints and scrums
• • Has specific domain knowledge and understands the market, customer, technology, data, AI and regulatory dynamics affecting the product, including the opportunities, limitations and risks of applying AI in a complex financial services environment
• • Experience with successfully managing projects with defined deliverables and budgets. Experience must include budgeting and managing the schedule; client relationship management; communicating strategically around key issues; conflict resolution and consensus building
• • Must have a thorough understanding of complex information systems and technology organizations and to be able to work effectively between the application, data infrastructure, operations and security architectural spaces
• • Proven delivery skills including the ability to scope/size a project; staff a team with the appropriate skill set; provide subject matter direction and guidance to a team; manage communications with the project sponsors and manage the delivery of an engagement workstream
• • Outstanding written and verbal communication skills
• • Requires domestic and regional travel up to 80% to serve client needs
• • Experience working alongside data, analytics or AI specialists to shape use cases, define outcomes and test AI-enabled features
• • Familiarity with product analytics, experimentation and evaluation methods, including approaches for validating the quality and usefulness of AI-generated outputs
• • Relevant product management, agile, design, cloud, data or AI training or certifications