Director, AI Transformation

Rare Beauty Brands is a prestige skincare company with a portfolio that includes Kate Somerville, Patchology, and Good Day. We are growing fast, and our strategy is clear: acquire and build mid-sized premium skincare brands that serve discerning consumers, and run them better than anyone else could. AI is now central to how we plan to do that. Rare Beauty Brands is an equal opportunity employer.

Rare Beauty Brands is hiring a Director, AI Transformation to move the company from using AI tools to running on them. The role reports directly to the President & CEO and works across every function: brand, digital and ecommerce, marketing, supply chain, finance, and people.

Most companies, RBB included, have adopted AI at the individual level: people use it to write faster, summarize, and draft. The next stage is different. It means redesigning how work gets done, building agents and automations into real processes, and measuring the return. Getting there takes a dedicated owner with the technical range to build it and the business judgment to know what is worth building.

That is this job. You will sit with each department head, find the friction in how their teams operate today, and then design, build, and ship solutions that remove it. Some of that work you will do yourself. Some you will do with vendors, agencies, and the people already on the team. All of it has to show up in scalability, efficiency, profitability, or growth.

Find the work worth transforming

• Partner with each member of the executive leadership team to map current workflows, pain points, and sources of friction in their functions

• Build and maintain a prioritized pipeline of AI and automation opportunities, ranked by business impact, effort, and risk

• Say no to shiny projects with no ROI, and be able to explain why

Build and ship

• Design, prototype, and deploy AI agents, automations, and integrations across our systems (ERP, ecommerce platforms, Amazon, CRM and email marketing, data and reporting tools, and the tools we have not bought yet)

• Do hands-on work yourself where it is faster, and direct vendors, agencies, or internal builders where it is not

• Own the technical architecture: how our tools connect, where data lives, how agents get access, and what guardrails are in place

Make it stick

• Lead the change management side: training, documentation, adoption tracking, and partnering with teams to redesign processes in ways that ensure adoption

• Build internal capability so the company gets more self-sufficient over time, not more dependent on you

Govern it

• Own AI governance at RBB and chair a small AI governance group (CEO, select members of the Executive Leadership Team, HR) that approves policy and signs off on higher-risk deployments

• Update and maintain RBB’s AI policy: acceptable use, approved tools, what data can go into which systems, brand safety for anything customer-facing, and where a human has to review before anything ships

• Run an agent and tool registry. Every agent, automation, and AI tool in use has a named business owner, a documented purpose, the systems and data it can touch, its cost, and a review date. Nothing goes live unregistered

• Set guardrails for agents that take action: least-privilege access, limits on what they can spend or change, logging, and a fast way to shut them off, especially when they touch customers, money, or inventory

• Protect company and customer data: classify what is sensitive, control who and what can access it, and run a security and privacy review on every AI vendor before we sign (how they store, retain, and train on our data)

• Get ahead of shadow AI: know which tools people are actually using, bring the useful ones into approved channels, and retire the risky ones

• Own the response when an agent gets something wrong, exposes data, or behaves unexpectedly: how it is caught, fixed, and reported

• Track the privacy and AI regulations that apply to RBB and keep us compliant without slowing the work down

Measure and report

• Define the metrics for every major initiative before it starts (hours saved, cost avoided, revenue lifted, cycle time cut) and report against them

• Give the CEO and ELT a clear, regular read on what is working, what is not, and what is next, including where AI risk stands: what is in the registry, what has been reviewed, and any incidents

• Stay ahead of the AI curve, continually and rapidly identifying disruption opportunities and translating complex breakthroughs into lean, high-velocity…