Staff Knowledge Base Specialist

About this role

About Checkr Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, Amazon, and Anthropic.

We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company .

About the team/role

As the Staff Knowledge Base Specialist, you will be a senior contributor to the knowledge systems that enable both Checkr's human and digital workers to resolve issues accurately and efficiently. This is a senior individual contributor role within Shared Services, responsible for leading complex, cross-functional knowledge programs that span department boundaries and directly shape the quality of agent-assisted and AI-driven resolution at scale. You will set strategy, clarify goals, and independently drive programs from initiation to measurable outcomes.

Knowledge at Checkr serves a dual audience: human agents who rely on clear, actionable content to resolve complex cases, and AI agents that retrieve, reason over, and act on that same knowledge base autonomously. This role requires mastery of both dimensions. You will design content that is clear and actionable for human agents while simultaneously being structured for accurate AI retrieval, optimized for fast search, and enriched with metadata that drives correct segmentation and response logic. You will also build, manage, and iterate on AI workforce agents that accelerate knowledge operations, treating them as members of your toolkit the same way you would a contractor or vendor.

Our ideal candidate brings a rare combination of disciplines: the precision of a technical writer, the systems thinking of an information architect, and the LLM fluency of a prompt engineer. You have hands-on experience building knowledge for RAG-based AI systems, a sharp instinct for the content gaps that cause agent escalations and model hallucinations, and the ability to drive alignment across engineering, product, quality, and operations partners. You thrive in ambiguity, mentor peers, and balance department impact with broader company objectives. You are startup-minded: comfortable building from scratch, owning ambiguous problems end to end, and leveraging AI agents as force multipliers to drive outcomes at a scale beyond what manual effort allows.

This role is based in Nashville, TN and requires periodic travel (

What you'll do

• Design and drive Checkr's agent-facing knowledge architecture: content structure, chunking strategy, metadata schema, retrieval optimization, and decision logic encoding for both human and AI agent consumption.

• Independently lead complex, cross-functional knowledge programs from initiation to delivery, coordinating with product, engineering, quality, and operations stakeholders to set strategy and achieve program goals within planned timeframes.

• Build, deploy, and manage AI workforce agents that execute knowledge operations tasks, including content audits, metadata enrichment, quality checks, and triage workflows, owning agent performance and iterating on prompts, logic, and guardrails to improve outcomes.

• Define and enforce authoring standards that serve a dual audience: content readable and actionable for frontline BPO agents, and structured for accurate, low-latency AI retrieval.

• Design and manage analytical workflows, including AI assisted triage, to surface knowledge gaps from escalation patterns, quality scores, and conversation failure logs.

• Proactively identify and anticipate risks and gaps in the knowledge ecosystem, including content that misleads agents, creates compliance exposure, or degrades AI performance; propose and execute next steps without waiting to be directed.

• Build and maintain metadata frameworks that ensure knowledge is correctly segmented across agent types, customer tiers, product lines, and support workflows.

• Partner with AI/Product and Engineering teams to surface knowledge-side limitations affecting agent and AI resolution quality, influence prompt design, and advocate for platform enhancements.

• Identify opportunities across agent and AI performance data to drive continuous improvements to content standards, knowledge architecture, and intake processes.

• Serve as a trusted cross-functional partner to Quality, Training, Service Design, and frontline operations teams, translating frontline agent experience needs into knowledge improvements.

• Mentor Knowledge team members on agent-aware and AI-aware authoring practices, providing clear, specific feedback and coaching to build team capability.

What you bring

• 5+ years of experience in knowledge management, information architecture, technical writing, or content operations, with demonstrated progression in scope and complexity.

• 2+ years of hands-on experience building knowledge for AI systems, including chunking strategies, metadata design, retrieval accuracy improvement, and hallucination reduction in a RAG-based environment.

• Experience designing content for a dual audience: human agents who need clear, scannable, actionable content and AI systems that require precision structure for accurate retrieval and reasoning.

• Hands-on experience building and managing AI agents or automated workflows (e.g., prompt chains, decision agents, RPA sequences) to execute operational tasks at scale.

• Proven ability to independently lead complex, cross-functional programs, balancing department priorities with broader company objectives and driving outcomes without direct authority.

• Fluency with leading LLMs (GPT-4, Claude, Gemini) and Gen AI concepts including RAG, agentic AI, chain-of-thought prompting, decision flows, and vector search.

• Strong syst

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