Engineer

AFLALO — Founding Team

Location : Remote / Global — In-House or Freelance considered for the right person

Compensation : Competitive base salary + founding team equity

How to Apply

Send a short written response — no more than one page — to [email protected] addressing the following:

• Walk us through a system you have built from scratch: what the problem was, how you architected the solution, and what you would do differently today.
• Include any relevant links (GitHub, portfolio, prior work) and a brief note on what draws you to this role specifically. We read everything.

We are not looking for a polished application. We are looking for how you think.

What We Are Building

AFLALO is an AI-first luxury fashion brand — built from the ground up with intelligence and automation as part of the operating model from day one.

Right now, that means evaluating and building the foundational infrastructure: a core SaaS stack across product, commerce, finance, and marketing — currently Shopify, NetSuite, Centric, and Klaviyo — and on top of it, a unified AI layer that connects these systems into a single, shared model for visibility, analysis, and decision support.

Where we are going is further. Long-term, AFLALO will be a technology-native luxury house — where advanced manufacturing, and material science amplify creative vision. We sit at the intersection of taste, luxury, and technology. The infrastructure we build should be as considered as the products it serves.

***We are early. The foundation is what this role is about.
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The Role

This is a founding technical role. There is no team beneath you yet, no architecture handed to you, and no roadmap waiting for sign-off. You will work directly with the founder to design and ship the operating infrastructure that makes this model real.

Right now, we have a core SaaS stack in place — Shopify, NetSuite, Centric, and Klaviyo — with no integrations between them. Your first job is to change that. Your broader job is to build the unified AI intelligence layer on top, deploy structured agents that automate execution, and establish the data governance standards that make everything reliable and auditable.

By the end of Year 1, the measure of success is clear: core systems are integrated and communicating, AI agents are handling repeatable operational tasks, a data governance framework is in place, and an AI-enabled design process is beginning to take shape. The business should be able to scale in revenue and complexity without scaling headcount proportionally.

One thing worth saying plainly: the team you would be working with is not technical, but they are deeply curious and already building their own AI solutions independently. Our creative team is already using AI in advanced ways across product design and image — pushing what the tools can do, not just adopting them. Every new hire at AFLALO is screened for AI fluency — it is a baseline expectation across the company, not just in this role. You will have genuine domain expert partners who lean in.

This role will also be shaped by you. We are intentionally leaving room for the right person to influence strategy, architecture decisions, and what we build next.

* What You Will Own
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Systems Integration & Orchestration Connect Shopify, NetSuite, PLM, and Klaviyo into a unified data and intelligence layer. Design the pipelines and APIs that allow these systems to share context reliably.

AI Platform & Infrastructure Build and maintain the core AI infrastructure — model usage, data access, version-controlled workflows, and monitoring. Ensure everything that runs in production is observable, auditable, and recoverable.

Agent Automation & Execution Deploy structured AI agents that automate operational tasks — updating records, triggering workflows, coordinating across systems — within defined rules and approval gates.

Data Governance & Quality Establish standards for data integrity, asset labeling, and forecasting accuracy. Prevent tool sprawl. Build the evaluation and monitoring that ensures the system stays trustworthy as it scales.

Technical Partnership Work directly with product, merchandising, marketing, and operations to translate business needs into practical automation. You are the bridge between what the business needs and what the system does.

What We Are Looking For

You have shipped production AI systems — not just prototyped them. You have debugged a broken pipeline under pressure and built the monitoring so it does not break the same way again. You think in repeatable systems. You move before you have a complete brief. You know when to ship and when to keep building.

Specifically, you bring:

• Proven experience building production-grade AI/ML pipelines and deploying agents in real operational environments
• Strong data and systems engineering — API integration, data modeling, pipeline architecture — across a modern SaaS stack
• Comfort with ambiguity and founding-stage pace — you define the problem as often as you solve it
• A bias toward governance and quality — you care that the system is accurate and auditable, not just functional
• The judgment to know when AI should act autonomously and when a human needs to be in the loop

This role is not for you if you need a detailed spec to get started, prefer research over deployment, tend to over-architect before shipping, or think of yourself primarily as a consultant rather than a builder with ownership.

The Standard

We use AI to protect human attention, not replace it. The systems you build handle scale and operational coordination so our people can focus on what defines the brand — curation, client relationships, and the judgment calls that cannot be automated. If that distinction matters to you, we are probably aligned.