Staff Knowledge Base Specialist

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 systems thinking: ability to trace how a knowledge gap, metadata error, or unclear procedure propagates into agent escalations, AI failures, and customer experience degradation.
• Analytical mindset with comfort reading quality scores, latency logs, and accuracy data to diagnose root causes and design targeted solutions.
• Track record of proactively identifying risks, leading retrospectives, and implementing process improvements that prevent recurring issues.
• Demonstrated ability to mentor and coach more junior team members; experience leading external contractors is a plus.
• Exceptional written communication: able to produce clear, actionable content for agent-facing audiences and translate complex AI-system concepts into standards and recommendations for varied stakeholders.
• Preferred: Experience with Zendesk or Salesforce knowledge bases.
• Preferred: Background in support operations or conversation design.