CX Knowledge Specialist

Pura•Pleasant Grove, UT

4d•Onsite

About The Position

The CX Knowledge Specialist role at Pura goes beyond writing and maintaining documentation to owning the health of Pura's Customer Care entire knowledge system. This includes how that knowledge powers both human agents and AI-driven support tools. This individual acts as a liaison between frontline support, subject matter experts, and the AI system. They are responsible for developing systems that track changes, address knowledge gaps before they become issues, and maintain a well-structured knowledge base for both human and AI use. The ideal candidate is a strong writer and trainer with an interest in AI, comfort with data, and a passion for building repeatable systems. This role offers an opportunity to make an impact in a high-growth company that is redefining the scent experience.

Requirements

2–4 years in training, documentation, knowledge management, or customer support.
Strong writing and editing skills, with the judgment to structure content for reuse, not just readability.
Experience with documentation tools, LMS, or knowledge base platforms required.
Exposure to AI-powered support tools (AI agents, chatbot, Claude, Gemini, ChatGPT or similar) and genuine interest in how content quality drives AI accuracy.
Ability to interpret basic performance data (escalation trends, fallback rates, content gap reports) to prioritize what to fix first.
Track record of running structured processes (audits, interviews, review cadences) not just responding to requests as they come in.
Comfortable partnering across Product, Engineering, Leadership, and other business stakeholders; able to represent Support's knowledge needs in cross-functional conversations.
Open to using AI tools to speed up their own work, with sound judgment about when human review matters.

Nice To Haves

ecommerce and/or subscription retailer experience is a plus, but not required.

Responsibilities

Develop, maintain, and update policy & procedure documentation across Customer Care.
Own Help Center content on the Pura website, partnering with stakeholders to ensure accuracy and quality.
Build modular, reusable content so updates propagate consistently across KB articles and macros instead of being rewritten one-off each time.
Run scheduled content health reviews with document owners; proactively identify drift between what's documented and what teams actually do.
Run structured methods to extract undocumented knowledge from experienced team members, SME interviews, shadow sessions with agents/reviewers.
Maintain a clear, visible process for submitting and resolving content gaps, so knowledge doesn't live only in people's heads.
Maintain active signal from the frontline back to documentation: synthesize escalation patterns, agent workarounds, and recurring errors that suggest the knowledge base is failing or drifting.
Act as an early warning system flagging knowledge gaps before they cause errors at scale, not after.
Report actionable insights to stakeholders (Support leadership, Product, Engineering,ect) to drive alignment on what needs to change.
Collaborate with the team(s) owning AI workflows to make sure they're drawing from accurate, well-structured content.
Identify performance gaps or broken AI experiences that trace back to content issues (missing info, ambiguous phrasing, outdated policy) and drive fixes.
Structure KB content with AI retrieval in mind so both human agents and AI tools get accurate answers from the same source.
Partner directly with Product and Engineering on AI custom answers/fallback content, using performance data to prioritize what gets fixed first.
Train BPO agents and internal staff on systems, processes, and support expectations.
Partner with leadership to ensure training content reflects evolving business needs and policy changes.
Translate decisions made at the strategy level (new product launches, policies and/or operational changes) into execution-ready guidance (decision trees, escalation paths, KB updates, etc) so nothing gets lost in translation between teams.
Take on a light, regular volume of support tickets to stay close to real customer issues and keep documentation and AI content grounded in actual user language and pain points.