AI Operator

This role is part of our Central AI Team at saas.group. What is saas.group? Think of us as the driving catalyst behind your favorite software success stories. saas.group, established in 2017, is on a mission to turbocharge promising B2B SaaS ventures, unlocking their full potential. As a Software-as-a-Service portfolio powerhouse, we specialize in acquiring small software treasures and polishing them into industry stars. With a dynamic, fully remote team of nearly 400 colleagues spanning 50+ countries we are truly global and we are rewriting the playbook on SaaS innovation and collaboration. We grow 25 exciting brands under our umbrella. Feel free to explore our Candidate's Hub to get an insider's view, dive into our culture, gain valuable insights into our teams and how we work. Also, don't forget to follow saas.group on LinkedIn to stay up-to-date on our job openings, podcast episodes, and with all things happening at our company. Profile Overview Our Central AI squad works along two paths: one makes sure we build production-ready AI systems into our brands' products; the other makes sure our teams work better, individually and together, with the help of AI tools and workflows. This role lives on that second path. We don't just advise on AI, we build it and put it to work inside real teams. As an AI Operator, you transform how our teams actually work, inside a single function and across functions (between, say, support, product and marketing), with AI as the orchestration engine. You embed with a brand or central function, watch how the work really gets done today, then redesign it with AI at the centre and make the change stick. Concretely, that can mean developing Claude or Codex skills, setting up n8n flows, and building smaller agents, whatever the redesigned process actually needs, then training the team and handing it over so they run it confidently without you. Each engagement is focused: you live and breathe one function for the two-to-four weeks it takes to reimagine it, then you move on and the brand owns it. You don't need to be an engineer to do well in this role. Some of the best people for this role come from product, operations, customer support, sales, consulting or project management, places where they've seen how the work really gets done. An engineering background is a plus, not a requirement. What matters is the operator instinct: finding the leverage, building it with AI, and getting people to actually adopt it. You won't be writing production software here, your craft is changing how a team works. Your immediate impact in the first 3-6 months will be: Your first transformation. Embed with one brand or central team, map and measure how the work runs today, redesign one real workflow with AI at the centre, and get the team actually using it, not piloted, adopted. A before/after worth showing. A measured change (time, cost, cycle time, or a capability the team didn't have) that a brand lead is happy to put their name to. The first reusable assets. What you build becomes a playbook and a skill the next brand starts from, instead of from scratch. Your responsibilities Discovery and baseline. Sit with a team, map how the work really gets done, find where it piles up and where quality breaks, and measure the starting point before you change anything. Build and implement. Write a tool-agnostic playbook for the redesigned process, then stand up the tooling it calls for: agents, automations, Claude/Codex skills, prompt libraries. Adoption, the make-or-break. Get the team to actually run the new way of working you built, including hands-on one-on-one coaching in their own setups. Most AI initiatives die here; making the change stick is the job, not the afterthought. Measurement. Measure success the way the team would, by adoption and measurable workflow impact: time saved, cost, cycle time, or a capability they didn't have before. Day-zero for incoming brands. For newly acquired brands, onboard the team into the tools and set up the core workflows and support from the start. What you bring to the table Agency, grit and drive. The one we screen hardest for. You see a gap, propose a fix, run a test, report back, without being told. You navigate ambiguity in a complex, multi-brand org, scope the work, and remove blockers without waiting for permission, with the delivery and time-management discipline to land a focused engagement on a tight clock. Current, hands-on AI fluency and orchestration. A hard requirement. You use Claude and/or Codex every day in real work; can explain in plain words what an MCP, a skill, an agent and a plugin are, and when to reach for each; already build the things that make a workflow run (Claude/Codex skills, n8n flows, small agents) and know how to check the output is actually right; and aren't blocked by the basics like Git, the terminal or n8n, resourceful enough to use AI itself to work through them. An operator's instinct for systems. You decompose a messy workflow into steps AI can run, you spot the structurally high-value thing (not just the easy one), and you have the taste to know what not to build. You design where AI runs on its own, where a human reviews, and what happens when it gets something wrong. Change management. You win a skeptical team's trust and actually change how they work, through doing real work alongside them and clear storytelling to skeptics and leaders alike. Your credibility is grounded in the work, not in being "the AI person", and you measure success by what the team adopts, not by what you personally build. Real domain ground and clear communication. You've done real work in a real function (we're looking for at least 4-5 years of professional experience overall) and can speak the language of the team you embed with. Fluent English is a must, and you can explain technical ideas in plain words anyone can follow. Most candidates won't tick every box. If you're high-ag