Senior Manager, AI Self-Service Content & Knowledge
BILL · San Francisco Bay Area
📍 Draper, Utah, United States; San Jose, California, United States; United States💰 $150,800via greenhousePosted 2026-06-15
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Innovate with purpose
At BILL, we believe in empowering the businesses that drive our economy. By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations. And we don’t stop there: we’re creating the future of financial automation so businesses can spend more time on what matters.
Working here means you become part of a vision-driven team that’s ready to tackle challenges and build cutting-edge solutions. We value purpose, drive, and curiosity—and we thrive in a fast-paced, ever-changing environment. Whether in one of our offices in San Jose, CA, Draper, UT, or in a remote-eligible role, BILLders collaborate to deliver real impact for businesses that need more time in their busy weeks.
BILL builds high performing teams and we seek to hire the best talent for every role. We're committed to building a workplace that fosters inclusion and diverse perspectives, valuing each person’s unique skills and experiences. We’d love to hear from you—you might be just what we’re looking for, whether in this role or another.
✨ Let’s give businesses more time for what matters.
Make your impact within a rapidly growing Fintech Company
The CXO AI Service Excellence & Operations team sits at the heart of BILL’s next-generation customer support experience, designing intelligent, AI-enabled journeys that help small and midsize businesses move money with confidence. As the Senior Manager, AI-First Self-Service Content & Knowledge , you will own the strategy and execution of our global knowledge ecosystem—the foundational “neural network” that powers the BILL Assistant and our AI Agent Assist tools. You’ll transform legacy documentation into an AI-optimized, Retrieval-Augmented Generation (RAG) environment that delivers fast, accurate, and trustworthy answers for customers and service representatives. This is a highly visible leadership role for a builder who thrives at the intersection of customer experience, artificial intelligence, and content governance.
Responsibilities:
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.
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.
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.
Implement and mature GenAI-assisted Knowledge-Centered Service (KCS) practices so knowledge capture, curation, and enrichment become a natural byproduct of every customer interaction.
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.
Orchestrate cross-functional alignment with Service Systems & Tools, IT, Product, and CX leadership to embed knowledge flows directly into platforms and ensure 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.
We’d love to chat if you have:
10+ years of proven leadership experience in content strategy, digital self-service, or customer experience operations, with a 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, including 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.
Visa Sponsorship: Please note that this position is not eligible for visa sponsorship. Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future.
Our ranges for each role and job level are based on a variety of factors including candidate experience, expertise, and geographic location and may vary from the amounts listed below. The role is also eligible for a competitive benefits package that includes: medical, dental, vision, life and disability insurance, 401(k) retirement plan, flexible spending & health savings account, paid holidays, paid time off, and other company benefits. The estimated salary ranges noted below roles in the specific geographic zones
Zone 1- San Francisco Bay Area CA (includes HQ), New York City, Seattle, Los Angeles County $150,800 — $188,200 USD Zone 2- CA (Non San Francisco Bay Area and Los Angeles County), Austin TX, Massachusetts $135,700 — $169,400 USD Zone 3 -Utah (includes Utah office), Houston TX, Florida, North Carolina $128,200 — $160,000 USD What’s in it for you?
Redefining how businesses automate their work is a fast-paced, exciting, and fun environment. But w
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