Senior Digital Product Manager

Charles Schwab Inc.•Raleigh, NC
•$117,300 - $170,000•Onsite

About The Position

Charles Schwab's Digital Retail product team is changing how clients use digital experiences. We use AI, search, and conversational platforms to make complex financial decisions simpler. You will join a high-impact group focused on Conversational AI, Enterprise Search, and Digital Support across web and mobile, including chat, voice, search, and help content. We're looking for a Senior Product Manager (individual contributor) to make sure our AI-powered client journeys are accurate, safe, and compliant. You will review AI evaluation outputs, find quality and risk gaps, and turn what you find into clear journey requirements. You will partner with product, engineering, data, design, risk, compliance, supervision, and service teams to deliver trustworthy experiences.

Requirements

  • FINRA Series 24 or Series 99 license
  • 5+ years of digital product management experience
  • Experience with support content, conversational AI, search, chatbots, or voice products
  • Experience in compliance-driven or regulated financial services environments
  • Strong experience writing PRDs and clear acceptance criteria
  • Strong analytical and problem-solving skills, with the ability to use data to drive recommendations
  • Ability to influence stakeholders and build alignment across teams
  • Agile experience (Scrum, backlog management, sprint planning)
  • Excellent written and verbal communication skills

Nice To Haves

  • Ability to evaluate and improve AI quality, performance and safety
  • Strong organizational skills, with the ability to manage multiple priorities
  • Experience with Workfront, Jira, Confluence, or Tableau
  • Understanding of content governance, accessibility, SEO/AEO/findability, metadata, taxonomy, content lifecycle management, or compliance-driven environments

Responsibilities

  • Review AI eval outputs, transcripts, and test results. Assess accuracy, grounding, hallucinations, tone, disclosures, and policy adherence.
  • Build and improve AI quality frameworks, including evaluation criteria, scoring rubrics, and acceptance thresholds.
  • Find failure patterns and root causes. Turn them into prioritized fixes and requirement updates.
  • Partner with supervision to ensure AI safety, governance, and responsible use.
  • Flag outputs that may create regulatory, suitability or client-harm risk.
  • Translate business goals, client needs, eval findings, and stakeholder feedback into requirements, user stories, acceptance criteria, and prioritized recommendations.
  • Write clear PRDs that define end-to-end journey behavior, including happy paths, edge cases, fallbacks, and handoffs.
  • Create process maps, gap analyses, issue summaries, and decision materials to help teams prioritize work.
  • Investigate client pain points and journey friction to find ways to improve self-service.
  • Keep a steady pipeline of delivery-ready work across multiple sprints.
  • Support backlog refinement, sprint planning, demos, validation, launch readiness, and post-launch optimization.
  • Track open issues, risks, blockers, dependencies, and decisions. Escalate items that may affect quality, compliance, or client experience.
  • Use experiments, transcripts, and analytics to keep improving experiences.
  • Influence stakeholders and drive decisions across multiple levels of leadership.
  • Weigh opportunities, constraints, risks, and trade-offs so leaders can make informed decisions.
  • Explain complex AI and technical concepts clearly to leadership audiences.
  • Provide consistent visibility into product performance, roadmap, and key decisions.

Benefits

  • bonus or incentive opportunities
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