Systems Lead, AI Engineer (Applied​/Software), IT​/Tech

Requirements

• You have 3+ years of experience in knowledge management, technical documentation, content systems, information architecture, content operations, or a related role, ideally in a complex B2B, technical, or regulated environment
• You think in systems. You care about how information is structured, maintained, searched, surfaced, and reused
• You have strong product and UX judgement. You understand that great user experiences reduce work for users. They make the right information easier to find, understand, and apply
• You are comfortable with complex subject matter. You do not need to be a regulatory expert, but you should be excited by the challenge of making regulatory expectations clearer without making them less precise
• You are technical enough to work closely with engineers. You may have experience with Markdown, Git Hub, docs-as-code, headless CMSs, structured content, developer documentation, or AI retrieval systems
• You are interested in how knowledge should be consumed by both humans and AI systems. You understand that AI-ready content needs structure, source clarity, version control, and careful governance
• Your verbal and written communication skills are exemplary, aligned with MECE principles and adapted to an asynchronous work environment

• Own the structure, navigation, and presentation of Scarlet’s customer‑facing knowledge base, making it easier for customers to find and apply the right guidance
• Create content models, templates, taxonomies, metadata, etc that make the KB easier to use, maintain, and extend
• Partner with subject matter experts to turn complex expectations into clear, structured guidance without losing precision or intent
• Use customer questions, search behaviour, and content performance to identify where the KB is confusing, incomplete, or too hard to act on
• Shape how Scarlet’s guidance can be surfaced across the product, anticipating changing usage patterns as AI capabilities rapidly evolve and preserving accuracy, nuance, and trust