New: Lake House Group Learning Hub — Explore practical AI ecommerce resources

Careers

Careers at Lake House Group

Contributing to the evolution of ecommerce on Shopify

At Lake House Group, we work at the heart of growing ecommerce.

Our mission is to support Shopify brands in modernizing, automating, and evolving their ecommerce, by combining human expertise and proprietary technology built on artificial intelligence. As a long-term partner and transformation accelerator, Lake House Group helps brands move forward continuously and improve at the pace of technological and market evolution.

We don’t operate like a traditional agency. Lake House Group acts as a long-term ecommerce and technology partner, embedded within client teams, with clear responsibility for the solidity, performance, and evolution of their Shopify ecosystem.

This vision guides both our work with brands and the way we build our team.

What to expect here

Our environment is built for people who want to make a real impact on ecommerce.

Ecommerce obsession

Catalog, operations, marketing, data, automation — you live and breathe the real challenges of Shopify every day.

Strategy meets execution

You connect ecommerce vision, technical implementation, and business impact in every project.

Systems thinking

You love structuring, analyzing, and improving complex systems to make them perform better.

Continuous growth

You thrive in environments where priorities evolve at the pace of brand growth.

Lasting impact

You’d rather build durable solutions than multiply isolated interventions.

Team context

What it means to work inside this ecommerce studio

The role of this page

the Lake House Group careers page is meant to give useful context before a commercial or operational conversation. It does not replace a diagnostic, but it helps candidates who want to understand the pace, standards, and type of work behind our client partnerships understand how we connect business goals, customer experience, the Shopify platform, marketing data, and execution constraints. The right decision is not only to launch a new page, automation, or campaign. The right decision is to identify which part of the ecommerce system is blocking growth and which change will create measurable progress without adding unnecessary complexity.

Our starting point

We start by clarifying how the business currently works: catalog structure, sales channels, customer segmentation, campaigns, inventory, internal team, tools, available data, and technical debt. That context changes the solution. Two brands can show the same public symptom, such as low conversion or low average order value, while having completely different causes. One brand can have a navigation problem, another an offer problem, another an email cadence problem, and another an operational bottleneck that slows execution.

What we protect

The work has to stay useful after launch. We prioritize structures the team can understand, maintain, and improve. That means reusable components, clean Shopify architecture, readable Klaviyo rules, dashboards that answer real questions, and automations that reduce workload instead of creating another fragile system. When AI is involved, it has to support a concrete decision or workflow. It should not sit on top of an unclear process and make the process look more advanced than it is.

How we judge quality

A strong ecommerce delivery is judged by several signals at once: execution speed, stability, user clarity, team autonomy, data quality, commercial performance, and capacity to learn. An interface can be attractive and still hard to operate. An automation can look impressive and still be impossible to control. A campaign can be well written and still poorly segmented. Our role is to connect these dimensions so the work holds up inside the daily reality of a commerce brand.

Why partnership matters

The brands we help rarely need one isolated task. They need a partner that can see dependencies between the site, email, operations, data, products, and internal priorities. A theme change can affect product discoverability. A new segment can affect campaigns, flows, and performance reporting. An AI workflow can require cleaner data before it produces a reliable result. The partnership keeps those links visible and prevents teams from solving one problem while creating another.

What to prepare

The best early conversations come with a few practical inputs: business goals, current friction points, examples of pages or journeys that feel weak, tools already in place, internal constraints, seasonal pressure, current metrics, and decisions that have stayed unresolved for too long. We do not need a perfect brief. We need honest context that helps separate real blockers from surface requests.

The logical next step

When the fit is right, we turn that context into concrete priorities: what should be fixed quickly, what deserves a structured project, what needs measurement before a decision, and what should be left alone. That discipline protects budget and attention. It also creates a plan that moves by evidence, not only by opinion or whatever trend is loudest at the moment.