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AI Digital Transformation Executive

CÔNG TY CỔ PHẦN MAISON RETAIL MANAGEMENT INTERNATIONAL ·
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Hồ Chí Minh, Quận 8

Tổng quan

  • Find where AI can remove manual, repetitive or slow work, by sitting with teams across all departments and watching how they work rather than relying on what a request form says.
  • Coordinate across departments to scope each initiative: agree what is being solved, who is affected, what data and system access is needed, and who signs off before building starts.
  • Design the solution: shape the flow, the screens and the experience so the tool is genuinely usable by non-technical colleagues.
  • Build it. Use AI-assisted development tools to go from idea to working prototype in days rather than months, then iterate with real users until it is good.
  • Ship internal tools, assistants and automations to production, and take responsibility for whether people use them.
  • Build automations and integrations that connect systems, using tools such as n8n and APIs to move data between e-commerce, CMS, ERP, CRM and third-party services.
  • Handle the unglamorous parts of a working system: error handling, retries, edge cases, monitoring, and fixing things when they break.
  • Evaluate new AI tools and models, run quick tests to see whether they solve a real problem, and recommend what is worth adopting.
  • Measure impact. Agree what success looks like before building, then show the time saved or the improvement delivered afterwards.
  • Keep stakeholders across departments informed: run working sessions and demos, report progress on active initiatives, and manage expectations on priorities and timelines.
  • Drive adoption: demonstrate what has been built, coach colleagues on prompting and usage, and follow up so tools do not go unused.
  • Document what you build clearly enough that someone else can pick it up, and support colleagues onboarding onto new tools.
  • Work with vendors and development partners where a build is beyond what can be done in-house.
  • Ensure all work follows Maison’s IT processes, standards and data handling rules.
  • A portfolio of things you have built. This matters far more to us than your degree or your job titles. Side projects, internal tools, automations, prototypes: show us and walk us through them.
  • Fluency with AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, Lovable, Replit or similar, and evidence you can use them to ship real working software.
  • Genuine feel for product and user experience: you can tell a good interface from a bad one, and you design for the colleague who will use the tool.
  • Solid understanding of how software works end to end (data, APIs, integrations, what breaks and why), whether you learned it formally or taught yourself.
  • Strong practical judgement with AI and Large Language Models: structured prompting and knowing where AI genuinely helps versus where it does not.
  • Comfort with workflow automation and integration concepts: triggers, conditions, branching, error handling and retries. Exposure to n8n, Zapier, Make or similar is a strong plus.
  • Ability to talk to business colleagues, understand what they need, and turn it into something working without a long specification process.
  • Curiosity and self-direction. This field changes monthly and we expect you to keep up on your own.
  • Good command of English for reading, writing and day-to-day communication.
  • No computer science or engineering degree is required. Candidates from any background, including self-taught, are welcome if the work speaks for itself.
  • Experience in e-commerce, retail or omnichannel operations is a plus, as is familiarity with platforms such as Haravan or Salesforce Commerce Cloud

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