Senior Manager, AI Service Design & Workflow Strategy- Advisor Services

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s). 

• Westlake: 3000 Schwab Way, Westlake, TX  76762
• Austin: 11800 Schwab Way, Austin, TX 78758
• Orlando: 70 S. Keller Rd, Orlando, FL  32810

As Senior Manager, AI Service Design & Workflow Strategy, you will help shape how advisors interact with Schwab by reimagining the workflows that connect advisors, associates, operations, digital platforms, and AI-enabled capabilities.

In this role, you will apply service design rigor to understand how work gets done across the RIA ecosystem. You will map end-to-end advisor journeys, uncover the internal human and system workflows that support those journeys, identify the behavioral and business problems that create friction or inefficiency, and translate insights into actionable requirements for Schwab’s AI Assistant and related advisor-facing AI capabilities.

This role sits at the intersection of service design, workflow strategy, process improvement, operations, analytics, and AI. You will partner across business, service, operations, product, UX, technology, data, and our broader AI team to improve advisor outcomes while increasing operational efficiency.

This is a highly visible role focused on discovery, service blueprinting, workflow strategy, requirements definition, stakeholder alignment, and scalable execution. It does not directly manage engineers or act as a Scrum Product Owner.

What You’ll Do

• Map end-to-end advisor experiences across digital channels, service interactions, operational processes, human handoffs, data inputs, and supporting systems.
• Develop service blueprints, journey maps, workflow models, and process artifacts that clarify how advisors, associates, operations teams, and technology platforms interact to deliver advisor outcomes.
• Use primary and secondary research, workflow observations, service metrics, operational data, digital analytics, and stakeholder feedback to identify high-value AI opportunities.
• Translate journeys, service design insights, operational findings, and data signals into business requirements, process improvement recommendations, AI use cases, and prioritization guidance.
• Identify the underlying behavioral, operational, and business problems driving advisor pain points before defining AI-enabled solutions.
• Recommend process improvements that reduce manual work, workflow complexity, service friction, avoidable servicing burden, and time to advisor outcome.
• Balance research rigor with speed by generating actionable requirements while discovery and validation continue.
• Define MVP-oriented requirements that deliver measurable value quickly and create a foundation for future enhancements.
• Work with immediate team members to shape innovative AI-enabled capabilities that address validated workflow, service, and business problems.
• Create repeatable frameworks, templates, intake methods, and playbooks so teams can document workflows and contribute requirements at scale.
• Facilitate working sessions, stakeholder interviews, requirements reviews, and cross-functional workshops with product, service, operations, technology, data, risk, and AI partners.
• Support prioritization by assessing advisor value, operational impact, scalability, implementation complexity, dependency risk, adoption potential, and measurable business outcomes.
• Communicate recommendations, tradeoffs, risks, and expected impact through concise, executive-ready materials.