Knowledge Manager - AI&Support Automation

<div><p>This is a remote position.</p><h3>About SiFi</h3><p>SiFi is building the future of spend management and financial operations in Saudi Arabia. Operating under SAMA EMI regulation, we manage complex financial products including card issuance, wallet systems, protected balances, multi-role admin environments, and cross‑border flows.</p><p>As we scale, automation is not optional — it is strategic.</p><p>To reduce operational dependency and enable AI‑driven support resolution, we are building a structured knowledge architecture that powers both customer self‑service and internal decision systems.</p><h3>Role Purpose</h3><p>You will be the architect of SiFi’s knowledge intelligence layer.</p><p>This role sits at the intersection of Product, Support, and AI. You will transform fragmented operational knowledge into structured, standardized, AI‑ingestible documentation that enables automated resolution of both customer and internal support queries.</p><h3>Your Mission</h3><p>Convert operational complexity into decision‑ready knowledge that machines can understand and execute.</p><h3>Key Responsibilities</h3><ol><li>External Knowledge Base Ownership (Customer‑Facing):<ul><li>Own and scale SiFi’s Help Center.</li></ul></li><li>Internal Knowledge Architecture (AI‑Optimized):<ul><li>Build and maintain structured internal documentation, including:<ul><li>Convert undocumented operational logic into actionable content.</li></ul></li><li>Design structured, standardized article formats (Problem – Cause – Resolution – Escalation) and develop AI‑friendly documentation with:<ul><li>Clear conditional logic</li><li>Step‑based instructions</li><li>Real‑world examples</li><li>Cover areas including:<ul><li>Card troubleshooting</li><li>Wallet limits&balance structures</li><li>Regulatory clarifications</li><li>Onboarding guidance</li><li>Maintain bilingual content (Arabic&English)</li><li>Add supporting visuals (screenshots, walkthroughs, short videos)</li><li>Support SOPs (L0–L2)</li><li>Decline reason logic trees</li><li>Edge‑case handling (e.g., excess wallet balance scenarios)</li><li>Customer segmentation logic (Starter vs Enterprise)</li><li>SAMA‑sensitive regulatory workflows</li><li>Escalation playbooks</li><li>Decision trees</li><li>Troubleshooting frameworks</li><li>Structured knowledge blocks ingestible by AI systems (3‑AI Knowledge Optimization&Deflection Strategy)</li><li>Map customer queries to knowledge articles</li></ul></li></ul></li><li>Identify failures (Failed responses, Low‑confidence outputs, Hallucination risks), analyze AI deflection rate, coverage gaps, and automation performance, and lead weekly Knowledge Sprints.</li></ul></li></ol></div>#J-18808-Ljbffr