AI Content Specialist

Responsibilities Conversation Optimization & Logic Design - Analyze user chat logs: review large volumes of conversational interactions to identify misinterpreted intents and user drop-off points. - Redesign problem flows: map logical, friction-free messaging paths to resolve recurring user confusion and guide users toward successful outcomes. - Continuous testing & tuning: test revised response paths in sandbox/staging environments to ensure new content triggers accurately before full deployment. Knowledge Base & Content Operations - Input & structure data: draft, format, and upload clear, structured information into the AI knowledge repository (databases, intent mapping software, or spreadsheets). - Audit knowledge assets: conduct regular quality assurance audits on existing responses to verify factual accuracy, eliminating outdated or conflicting information. - Standardize response quality: ensure automated outputs adhere to formatting guidelines, clarity standards, and correct grammar. Localization & Language Intent Decoding - Decipher informal inputs: interpret user messages written in informal, conversational Malay, local slang, abbreviations, or mixed-language (Manglish/Bahasa Rojak) text. - Context mapping: map informal inputs to the correct structural intent so the AI recognizes user queries regardless of phrasing. - Localized tone crafting: write culturally relevant, localized responses that feel natural and approachable to regional users. Cross-Functional Collaboration - Product & tech alignment: work alongside developers and product leads to report recurring system edge cases, bugs, or technical intent misfires. - Performance tracking: track key operational metrics (e.g., resolution rates, intent accuracy, user satisfaction scores) to measure the impact of content updates.