Location: Mexico (preferred) | Hybrid / Remote

About Sarelly

Sarelly is building more than a beauty brand — we're building an entertainment and culture-driven beauty company designed for the next generation of Latina consumers.

As we scale across Mexico and the U.S., we're investing in AI and data infrastructure as a core business capability — connecting the systems that run the business, automating repetitive work, and building intelligence systems that help our teams make faster, better decisions.

We're splitting what was originally a single "AI + Consumer Intelligence" hire into two focused roles. This posting is for the technical / operational half : the person who architects and builds Sarelly's automation and AI agent capability across the business. A separate Consumer Intelligence Lead will own the consumer questions, taxonomy, insight validation and translation into Product, Brand and Growth decisions. This role will partner closely with them to build the data collection, infrastructure and AI workflows that make that intelligence possible.

The Opportunity

This is not a traditional IT, data engineering, or "prompt engineer" role.

You'll architect the data and intelligence infrastructure behind Sarelly's decision-making: connecting internal business data with selected external market, consumer and competitive signals, and building systems that can turn that data into reliable, traceable intelligence

You'll be Sarelly's internal AI Champion : the person who knows what's actually possible with today's AI tools, pushes back when it isn't, and educates the rest of the organization so people stop guessing. You'll also be hands‑on — designing and shipping the automations,



integrations and agents that remove manual work across Operations, Logistics, HR and beyond.

Your mission: build the data, automation and AI infrastructure that makes Sarelly smarter and more efficient — connecting fragmented systems, eliminating repetitive work, and transforming internal and external data into reliable intelligence teams can act on.

You’ll report into the COO’s org and work directly with department heads (Supply Chain, Finance, Sales and Marketing) to find, prioritize and build these projects.

Key Responsibilities Be Sarelly's AI Champion

- Act as Sarelly's internal expert on what AI can and can't realistically do, helping teams identify and prioritize high‑value use cases.
- Build a culture where teams bring business problems, not tool requests.
- Create practical standards, reusable workflows and training so teams can safely use and build with AI while critical systems remain governed.
- Own and maintain a prioritized roadmap of AI, automation and data opportunities based on business impact, feasibility and effort.

Build Sarelly's Connected Data Foundation

- Ex Unify Sarelly's Inventory & Systems Data. Day One problem: Sarelly's inventory currently lives across disconnected systems — Shopify (website + offline stores in Mexico), two separate 3PL systems (MX and US), and Amazon (US and MX) — none of which talk to each other today.




- Design and build the integration layer that connects these systems into a single source of truth for inventory.
- Identify the next systems that should be integrated as the business grows.

Build Sarelly's Intelligence Infrastructure

- Partner with the Consumer Intelligence Lead to build the technical foundation of Sarelly's Consumer Intelligence Hub.
- Design data collection pipelines across selected public and first‑party sources, including social platforms, retailers, competitors, creators/influencers, customer feedback, commerce and CRM.
- Build systems capable of continuously transforming large volumes of unstructured data into structured, searchable intelligence using Sarelly‑defined taxonomies.
- Ensure AI‑generated outputs retain links to underlying source evidence, expose confidence and coverage gaps, and can be reviewed or corrected by human experts.
- Design the architecture so Sarelly owns its data and can connect it securely to Claude, ChatGPT or future AI models and agents without rebuilding the underlying system.
- Over time, extend this infrastructure beyond Consumer Intelligence to broader Business Intelligence, connecting commercial performance, retail, market/category forecasts and competitive intelligence to support leadership and country GM decision‑making

Build Automations, Agents & Internal Tools

- Map manual, repetitive or disconnected processes across the organization and determine where automation, integration or AI can create meaningful business value.
- Own these automations end‑to‑end: build, test, deploy, monitor, and fix when they break.
- Design and deploy Slack‑ba

📌 AI Architect — Data, Automation (México)
🏢 SARELLY
📍 México