About us 

••••••••••••• designs, sources and distributes children's apparel for some of the world's best-known brands, including Nike, Jordan, Converse and Levi's, and sells through major retailers worldwide. We are building an AI Engineering team, growing to seven people, to bring AI and fast, modern software into how the business works. 

We are not a research lab. We build on vendor models such as Claude and Microsoft Copilot, connect them to our Microsoft and data estate, and ship tools that people rely on every day. 

The role 

You lead the AI Engineering team and you still build, roughly half and half. You inherit a working AI platform and two platform engineers. You will grow the team with business analysts and fullstack developers. 

Your most important job is judgement. Many requests reach us labelled "AI" because the idea was worked up in ChatGPT or Copilot, but the right solution is ordinary, deterministic software. You decide what each request should become: an agent, a skill, an app, an automation, a job for another development team, or nothing. Then you make sure it is built one consistent, secure and measurable way. 

What you'll do 

  • Lead and grow the team. Manage platform engineers, business analysts and fullstack developers, and help hire the rest of the team. 

  • Own the technical call on every request. Decide whether it needs AI at all, and default to the lightest thing that works. Agents and skills where AI adds judgment; plain code, automation or a report everywhere else. 

  • Route work beyond your team. Larger builds tied to a business system go to our domain development teams (PLM, ERP, Photo Studio, workflow and Java). Agree the handoff with them and make sure routed work is picked up. 

  • Set the standards. Architecture, design review, security and access, CI/CD: one way of doing things across the team. 

  • Put evaluation at the centre. Build regression testing and monitoring for AI output, so a change is shown to be better, not just different. 

  • Run what we ship. Own reliability, support and cost per workflow, and retire solutions that no longer earn their keep. 

  • Build hands-on. Agents, integrations and platform components. 

  • Work with the business analysts, who bring measured, scoped problems and a baseline to judge results against. 

What you'll bring 

  • Production experience with LLM systems. You have shipped and operated agent or LLM solutions that real users depended on, not just prototypes. Be ready to tell us about something that broke and how you fixed it. 

  • Evaluation practice. You have built tests or evaluation harnesses for non-deterministic output. 

  • Strong software engineering beyond AI. You know when a problem needs a model and when it needs a well-built app, integration or rule, and you can build both. 

  • Platform depth. Environments, secrets management, identity and role-based access, CI/CD. 

  • Microsoft ecosystem fluency. Entra ID, Microsoft 365, SharePoint, and Microsoft Fabric or the Azure data stack. 

  • An integrator's mindset. You build on vendor models and APIs rather than training your own. 

  • Leadership while building. You have led 2–6 engineers and still shipped code yourself. 

  • Cost awareness. You can reason about spend per workflow, not just per licence. 

  • Strong written and spoken English. 

Nice to have 

  • Apparel, retail or consumer-products experience 

  • Experience coordinating work across several development teams or vendors 

  • Exposure to Power Platform, WEBCON, UiPath or other workflow and automation tools 

  • Experience handling personal data and data classification in AI systems 

  • Having introduced review, support or retirement processes for internal software 

  • Polish language skills (part of our technology team is based in Poland) 

Your first year 

3 months: The existing AI tools are secured, monitored and have a support path. Every incoming request gets a clear technical call. 

6 months: Evaluation is in place for every AI solution in production. Handoffs to the domain development teams work in practice. 

12 months: A team of up to seven ships on shared standards, and each solution has a known cost and a measured result. 

How we interview 

No puzzles. We give you real problems from our business: an AI answer that is close but not quite right, a portfolio of internal AI tools that needs securing and running, and a request for "AI" that may not need AI at all. We want to hear how you would think them through. 

Why join 

You will shape a new function from the start, with a working platform already in place, a clear mandate from leadership, and a business full of problems worth solving. 

Recruitment:

Introductory meeting (main) – one hour – teleconference with the Head of the IT Department, conducted in Polish. A short switch to English will be used to verify communication skills. During this meeting, we also discuss technical scope, responsibilities, and expectations on both sides.

Second meeting (approximately one week after the first conversation, unless agreed otherwise) – in case of mutual interest, we finalize technical details and employment terms.

Meet ••••••••••••• Promotional Video: Gofile - Share file links quickly and easily

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