AI Engineer

About the company Our client is a lean, founder-led venture-building studio and family office running a portfolio of businesses across events, hospitality, luxury consumer, media, and investments. The company is building AI-first operating systems so a small team can run multiple businesses at once — removing repetitive admin, improving decision-making, and keeping headcount deliberately low. Why this role exists The studio needs one hands-on technical owner for AI and automation across the whole portfolio. Some automations already exist; the mandate is to take them over, rebuild what needs rebuilding, and own a clean, maintainable stack end to end. There is no technical manager above you — you work directly with the founder and the commercial lead, and the architecture decisions are yours. This is a builder role — the person ships working systems the business actually uses — reliable agents and automations that hold up in production. What you'll work on AI development & automation — 80% AI research agents: vendors, sponsors, guests, brands, venues, market opportunities Screening and scoring systems that combine scraped data with hard metrics and business criteria Inbox triage, summarisation, and routing; multi-inbox monitoring with decision-ready daily summaries Systems that turn unstructured founder inputs (screenshots, voice notes, links) into recommendations and routed tasks CRM and outreach workflows, dashboards and trackers, calendar and recurring-task automations No one has built all of this — what matters is a track record with comparable use cases and the ability to transfer it to new problem types. Expect a fast cadence: first automation live within 30 days, several production workflows by 60–90 days. Technical generalist — 20% (~1 day/week) Keep the operational stack running: Notion (incl. Notion AI), Google Workspace, HubSpot, access management, integrations, troubleshooting, data cleanup Requirements Shipped production automations or AI-powered tools in a real business context — not side projects, demos, or hackathon builds Practical fluency with LLMs, APIs, and at least one automation platform (Make, n8n, Zapier, or similar) Python or equivalent scripting ability — many builds are achievable low-code, but candidates who can write and debug their own scripts have a higher ceiling Experience with vector search, RAG, agent frameworks, function calling, and workflow orchestration Ability to design workflows with human approval points, exception handling, logging, and error recovery — systems that fail gracefully and visibly, not silently Strong documentation habits — your systems must be maintainable and understandable by non-technical colleagues Comfort with ambiguity, shifting priorities, and working independently without full specs or a technical escalation path English sufficient for daily written and spoken communication (B2+) Nice to have Experience building internal tools for executives, family offices, venture studios, agencies, or lean startups HubSpot or comparable CRM experience Location requirements Fully remote, but your working day must overlap with UK time (GMT/BST) for 6–8 hours daily An additional ~2-hour overlap with Malaysia time (GMT+8) is a plus What to expect Greenfield mandate: build and own the AI stack; genuine autonomy, no stakeholder committees Cross-portfolio ownership — your systems run real businesses across events, media, luxury, and investments Direct access to the founder from day one; radically lean process: a call a decision execution An expanding role: new ventures continuously add projects, with the prospect of support hires under you as the stack grows Interview process Recruiter screen (incl. a short portfolio example of an automation you built) Interview with the client Practical assessment Final interview with the founder Terms Remote-first contractor engagement; own equipment required 28 days PTO per year, taken freely — covers vacation, sick leave, and holidays in a single policy Business travel expenses covered when required