Role Description This is a frontline operations role for an AI-native consulting practice. The founder owns each client engagement and sets the architecture. You keep the systems running and the clients well-served. As AI lets very small teams deliver work that used to require very large ones, someone has to make sure the prompts, knowledge bases, capture routines, and recurring deliverables behind that actually work as intended. What you'll do: Frontline support: Be the first point of contact for client teams. Take in requests, respond, escalate to the founder when needed. Diagnose the problem: Most requests won't come with clear specs. Figure out what the client actually needs and what the response should look like. Update the tooling: Once you know the right response, go into Notion, Linear, Slack, Google Workspace, Claude, Fireflies, etc. and make it real. The work is configuration and curation. Turn messy material into useful artifacts: Transcripts, email threads, scattered documents — read them, find the structure, produce a summary, decision log, brief, or procedure. Steward the knowledge base: Keep each client's institutional memory layer organized, current, and trustworthy. Catch staleness, gaps, and drift before they compound. Monitor quality: Review AI-assisted outputs on a regular cadence. Fix wrong-voiced or thin output and feed corrections back into the templates. Document the system: Write the procedures and reference materials that let a client's team operate on their own. Onboard new clients: Stand up tooling, ingest context, build initial structures, get routines running. Each onboarding makes the next one faster. Qualifications You're wired for correctness: You can't comfortably walk away from something that's half-finished or quietly broken. You learn by doing: You take a stab at tasks and return with a precise account of what you don't understand. You teach yourself the frontier: You explore new tools, features, and techniques on your own time. You want to own outcomes: You understand that owning something means defining success and being measured against it. You can understand what people actually need: You're good at translating messy requests into actionable tasks. You do not need a finance background or a degree: You need to be smart, curious, easy to work with, and genuinely interested in the problem. Requirements This role is about operating and wielding advanced AI systems — not building them. You will not be asked to code or derive any math. You need enough conceptual fluency to know what these systems are doing and when they're going wrong. Before you apply, spend an afternoon getting the gist of three things: Evals and traces, GraphRAG / Hybrid RAG, Auto-research loops. You don't need to understand how it works under the hood, but you should grasp the value and picture how you'd operate these in practice. A Litmus Test (Read Before you apply) If after an afternoon you can honestly say "I don't know how it works under the hood, but I get what it's for and how I'd use it" — you'll thrive here. If it's all still fog after a real attempt, this probably isn't the right seat, and that's genuinely okay.
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