Senior Manager, Product AI Enablement

Charles Schwab Inc.•Orlando, FL

2d•$120,000 - $185,000•Onsite

About The Position

The Transformation Management Office (TMO) at Schwab defines, leads, and accelerates large, cross-enterprise transformations that drive meaningful business and client outcomes. As Senior Manager, Product AI Enablement (individual contributor), you will help shape how Product leverages AI, by turning emerging capabilities into practical workflows, tools, and standards that enable teams to move faster, make better decisions, and deliver measurable value. You will own a workstream for the enterprise effort to evolve Product ways of working across product and software development lifecycles, including AI-enabled and AI-driven product development lifecycles (AIDLC). Working with cross-functional partners, you will identify high-value opportunities, clarify Product responsibilities and decision rights, and translate AI capabilities into repeatable practices from opportunity framing and discovery through planning, development, validation, launch, and measurement. You will build, test, and scale Product standards, playbooks, role guidance, capability expectations, and reusable assets that support responsible AIDLC adoption across different product areas and levels of maturity. You will partner with Product, Engineering, UX, Data, Architecture, Risk, and Business leaders to embed these practices into planning, delivery, governance, tooling, talent, and learning programs without creating unnecessary process. Through pilots, prototypes, practitioner feedback, and telemetry, you will test assumptions, evaluate adoption, identify friction, and refine what works. You will help teams determine where AI can accelerate Product workflows, where human judgment and accountability remain essential, and how workflow changes translate into measurable improvements in quality, speed, capacity, client experience, and business outcomes. Success in this role means Product teams can confidently apply AI-enabled practices, use practical tools and guidance, and remain accountable for strategy, outcomes, quality, risk, and client value. The solutions you help establish will scale across the enterprise, evolve as AI capabilities mature, and strengthen how Product and Technology teams build, learn, and deliver together.

Requirements

Bachelor’s degree; equivalent relevant experience will also be considered
5+ years of experience across product management, product operations, product enablement, or transformation, with strong end-to-end Product expertise spanning discovery, prioritization, requirements, delivery, launch, and outcome measurement
2+ years of experience applying AI-enabled or AI-driven approaches to product development, including identifying high-value use cases, evaluating emerging capabilities, and translating them into practical Product workflows
Working knowledge of context engineering and AI-ready product documentation, including approaches for research and information synthesis, enterprise knowledge retrieval, memory systems, context libraries, and business capability maps
Experience evolving traditional user stories into structured, reusable specifications, such as context packs or specification kits, that give AI tools and agents the goals, business rules, source knowledge, constraints, evaluation criteria, and acceptance criteria needed to produce reliable outcomes
Experience using pilots, practitioner feedback, product and operational data, and measurable outcomes to prioritize opportunities, test assumptions, evaluate adoption and business impact, and continuously improve solutions

Nice To Haves

Advanced degree in engineering, technology, business or a related field
High emotional intelligence and strong facilitation, communication, and influence skills, with demonstrated ability to listen actively, build trust, navigate conflict constructively, adapt to diverse perspectives, and align stakeholders in a complex matrixed environment

Responsibilities

Own and lead a defined AIDLC workstream, identifying high-value opportunities and establishing clear Product responsibilities, decision rights, quality expectations, and cross-functional collaboration points across the end-to-end lifecycle.
Build, test, and scale Product standards, playbooks, templates, maturity guidance, and reusable assets that strengthen problem framing, requirements, prioritization, trade-off decisions, risk management, and outcome measurement while allowing appropriate flexibility across products and delivery models.
Partner with Product, Technology, UX, Data, Architecture, Risk, Business, and talent leaders to integrate AIDLC standards into operating models, governance, planning, delivery practices, tooling, performance measures, role expectations, and learning programs.
Own a defined component of the roadmap for AI-driven tools, platforms, agents, and skills that support Product workflows, translating practitioner needs into requirements and prioritizing capabilities based on user value, strategic alignment, feasibility, risk, and expected business impact.
Clarify how AI tools and agents reshape Product workflows, defining where automation can accelerate work, where human judgment and accountability remain essential, and what responsible-use controls, validation, skills, and adoption support are required.
Lead pilots, prototypes, and continuous learning cycles that test assumptions, evaluate adoption, and measure improvements in quality, speed, capacity, client experience, and business outcomes; translate evidence and practitioner feedback into roadmap decisions and scalable improvements.