Senior Manager, AI Self-service Content & Knowledge

Bill.com Bill.com · Fintech · United States · Customer Experience Operations

Senior Manager role focused on AI-First Self-Service Content & Knowledge for a Fintech company. The role owns the strategy and execution of the global knowledge ecosystem, which powers AI Assistant and AI Agent Assist tools. Responsibilities include architecting AI-ready content structures, governing knowledge taxonomies, implementing GenAI-assisted KCS, defining KPIs, and orchestrating cross-functional alignment. Requires leadership experience in content strategy/CX operations with specific experience in enterprise Knowledge Management, generative AI concepts (RAG, LLM optimization, semantic search), knowledge taxonomies, and KCS principles.

What you'd actually do

  1. Own and execute the end-to-end strategy for BILL’s dual-surface knowledge ecosystem across the customer-facing AI Support Agent, Help Center, and internal AI Agent Assist experiences.
  2. Architect and continuously refine AI-ready content structures (including semantic chunking, templates, and conversational patterns) to maximize LLM ingestion quality, RAG performance, and semantic search effectiveness.
  3. Design and govern enterprise knowledge taxonomies, metadata standards, and content lifecycle processes to reduce duplication, prevent hallucinations, and ensure content is accurate, highly personalized, compliant, and trustworthy.
  4. Implement and mature GenAI-assisted Knowledge-Centered Service (KCS) practices so knowledge capture, curation, and enrichment become a natural byproduct of every customer interaction.
  5. Define, monitor, and act on a robust KPI framework (e.g., AI containment, first-contact resolution, CSAT/NPS, handle time, and content health) to drive continuous improvement in self-service and assisted-service outcomes.

Skills

Required

  • 10+ years of proven leadership experience in content strategy, digital self-service, or customer experience operations
  • minimum of 3+ years specifically directing enterprise Knowledge Management strategy in a fast-paced SaaS or FinTech environment
  • Proven track record of implementing generative AI concepts and tooling at scale
  • hands-on experience deploying RAG architectures, LLM optimization, semantic search, and designing content specifically for AI and agent assist use cases
  • Demonstrated success designing and managing enterprise-level knowledge taxonomies, metadata models, content chunking strategies, and governance frameworks that ensure accuracy, consistency, and compliance
  • Subject matter expertise in KCS principles with prior ownership of embedding knowledge capture and reuse into frontline workflows, specifically within AI-assisted or automation-rich environments
  • Demonstrated ability to lead cross-functional initiatives and teams—setting a clear vision, driving change management, communicating effectively at all levels, and using data and experimentation to prioritize and make decisions

Nice to have

  • AI-optimized content structures
  • semantic chunking
  • conversational patterns
  • LLM ingestion quality
  • RAG performance
  • semantic search effectiveness
  • enterprise knowledge taxonomies
  • metadata standards
  • content lifecycle processes
  • reduce duplication
  • prevent hallucinations
  • content is accurate, highly personalized, compliant, and trustworthy
  • knowledge capture, curation, and enrichment
  • AI containment
  • first-contact resolution
  • CSAT/NPS
  • handle time
  • content health
  • cross-functional alignment with Service Systems & Tools, IT, Product, and CX leadership
  • embed knowledge flows directly into platforms
  • new products, features, and AI “transaction agents” launch with fully pre-ingested, production-ready knowledge
  • Lead and develop a high-performing team of knowledge specialists and content designers
  • fostering a values-driven culture that is humble, authentic, passionate, accountable, and fun

What the JD emphasized

  • AI-First Self-Service Content & Knowledge
  • AI Agent Assist tools
  • Retrieval-Augmented Generation (RAG) environment
  • GenAI-assisted Knowledge-Centered Service (KCS) practices
  • AI “transaction agents”
  • minimum of 3+ years specifically directing enterprise Knowledge Management strategy
  • hands-on experience deploying RAG architectures, LLM optimization, semantic search
  • Subject matter expertise in KCS principles

Other signals

  • AI-First Self-Service Content & Knowledge
  • AI-enabled journeys
  • foundational “neural network” that powers the BILL Assistant and our AI Agent Assist tools
  • transform legacy documentation into an AI-optimized, Retrieval-Augmented Generation (RAG) environment
  • GenAI-assisted Knowledge-Centered Service (KCS) practices
  • AI “transaction agents”