AI Architect — Data, Automation & Intelligence Systems

SARELLY; México; Híbrido; MXN 900.000 - 1.800.000; Jornada completa

Descripción de la vacante

Sarelly is seeking an AI Champion to architect and build the automation and data‑infrastructure powering our decision‑making. You will connect internal data with external signals, design scalable AI workflows, and own the end‑to‑end automations across Operations, Logistics, HR and beyond.

You'll partner with the Consumer Intelligence Lead to create a robust data collection pipeline, transform unstructured data into structured intelligence, and ensure sources are traceable.

Formación

• Experience shipping AI-powered automations, integrations or data products in live environments.
• Hands-on experience connecting systems through APIs and building data pipelines.
• Strong experience with LLMs and AI agents beyond prompting.
• Knowledge of AI quality, source traceability and human validation.
• Ability to design maintainable, model-agnostic systems.

Responsabilidades

• Architect the data and intelligence infrastructure for decision-making across the business.
• Build and ship automations, integrations and agents that reduce manual work.
• Design Slack-based agents for quick internal answers (regulatory, order status).
• Collaborate with business teams to translate problems into technical solutions.

Conocimientos

AI automations

API integrations

LLMs & AI agents

AI quality & evaluation

System design

Cross-functional collaboration

Bilingual English/Spanish

Herramientas

APIs

n8n

Zapier

Make

Retool

Shopify

WMS/3PL systems

Amazon integrations

Descripción del empleo

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‑based agents that give the team fast answers on things like regulatory questions and order status/tracking.
• Identify other repeated, answerable questions across the org that an agent could handle reliably.

Build Business Intelligence & Forecasting Capabilities

• Help build a more robust demand planning and forecasting model.
• Organize the underlying data correctly so forecasting is reliable, not ad‑hoc.
• Automate recurring planning routines that are currently manual.
• Connect internal performance data with relevant external market, category and competitive signals to improve forecasting and business decisions.
• Partner with Finance, Sales and country GMs to identify recurring decisions that can be supported by better data, predictive models or AI‑assisted analysis.
• Build dashboards, alerts or AI‑assisted decision tools where they create measurable value — not dashboards for the sake of reporting.

What you bring

• Proven experience shipping AI‑powered automations, integrations, data products or internal tools in a live business environment — not just prototypes or experiments.
• Hands‑on experience connecting systems through APIs and building data pipelines across structured and unstructured internal and external sources.
• Strong hands‑on experience with LLMs and AI agents beyond prompting, including orchestration, function calling, RAG, tool use, structured outputs or similar production workflows.
• Strong understanding of AI quality and evaluation, including source traceability, confidence, human validation, error monitoring and failure modes.
• Ability to design maintainable, model‑agnostic systems, so critical data and workflows are not locked into a single AI model or vendor.
• Strong technical judgment: you know when to use generative AI, deterministic automation, traditional analytics, predictive models or a simpler process solution.
• Ability to translate messy business problems into practical technical solutions, prioritize based on business impact, and explain technical trade‑offs clearly to non‑technical stakeholders.
• Strong cross‑functional collaboration skills, with experience working directly with business teams to define requirements, build solutions, drive adoption and continuously improve them.
• Fluent in English and Spanish.

Preferred Experience

Strong preference for candidates with experience in one or more of the following:

• Retail, e‑commerce, supply chain or logistics technology, including Shopify, WMS/3PL systems, Amazon integrations, demand planning or forecasting.
• Workflow automation platforms such as n8n, Zapier, Make or Retool.
• Business Intelligence and data visualization, including dashboards, predictive models or decision‑support tools.
• Building production Slack, chat‑based agents or other internal AI tools

Mindset

We're looking for someone who:

• Ships working automations, not proposals.
• Is honest about what AI can't do yet, not just what it can.
• Gets energized by messy, disconnected systems and wants to fix them.
• Can work independently across multiple departments without losing focus.
• Wants to build a capability — internal AI/automation — that doesn't fully exist at Sarelly yet.
• Prioritize ruthlessly — focus on projects with clear, measurable operational impact.

Why Join Sarelly?

This is a rare opportunity to build Sarelly's internal data, AI and automation capability from the ground up — not as a side initiative, but as core infrastructure the whole company will run on. You'll have direct visibility into Supply Chain, Retail, Logistics, Customer Service and HR, and the mandate to fix real operational problems with real tools, fast.