New opportunity

Associate, AI Automation & Prototyping

Shopee · Singapore

About this role

This role sits within Shopee’s Regional Brand & Growth, AI Traffic team in Singapore. The Associate helps the SEO & GEO team reduce manual effort and scale output through AI agents and automation. The work starts with understanding existing processes and pain points, then building proofs-of-concept for a dedicated product and engineering team to take into production.

Responsibilities

  • Speak with SEO operators and marketing stakeholders, map how work is done, and identify bottlenecks and useful automation opportunities.
  • Independently design and build working MVPs and proofs-of-concept using no-code or low-code tools, prompt engineering, agent frameworks such as n8n, or similar approaches.
  • Document workflows, system logic, and requirements clearly enough for the development team to build reliably.
  • Maintain a prioritised backlog of automation and agent opportunities across the SEO organisation, incorporating team feedback and changes in AI tooling.
  • Stay current with AI agents, automation platforms, and workflow tools, and bring practical ideas to the team.

Requirements

A bachelor’s degree in any field and at least 1 year of experience in digital strategy, product management, or digital operations. Candidates must be able to gather user insights independently through conversations and process mapping, turn findings into recommendations, use AI tools such as ChatGPT or Claude in day-to-day work, and build prototypes independently. Strong communication across operators, marketers, product teams, and engineers is required. A master’s degree is advantageous but not required. Familiarity with n8n, Make, Zapier, or equivalent workflow platforms; experience with process mapping or blueprint methodologies; and exposure to SEO, digital marketing, or content operations are pluses.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI agentsAutomationPrototypingNo-code developmentLow-code developmentPrompt engineeringn8nMakeZapierChatGPTClaudeWorkflow documentationProcess mappingRequirements gatheringUser researchLightweight scriptingSEODigital marketingProduct managementCommunication

Your skill match

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Get interview-ready for this role

A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Discover the real workflow before building

    Source-backed: The role starts with conversations with SEO operators and marketing stakeholders, process mapping, and identifying manual effort and bottlenecks. The posting explicitly says building comes after discovery.

  • Build working automation proofs-of-concept

    Source-backed: Independently create MVPs using no-code or low-code tools, prompt engineering, agent frameworks such as n8n, or similar approaches to demonstrate proposed solutions for the SEO & GEO team.

  • Make the handoff usable by product and engineering

    Source-backed: Document workflows, system logic, and requirements clearly enough for the dedicated product and engineering team to take a proof-of-concept toward production without repeated clarification.

  • Prioritise opportunities across SEO

    Source-backed: Maintain a prioritised backlog of automation and agent opportunities, incorporating ongoing team feedback and changes in AI tooling.

  • Turn new AI tools into practical ideas

    Source-backed: Stay current with agents, automation platforms, and workflow tools, then bring relevant developments back as ideas the team can act on.

Likely challenges to think through

  • Resisting a solution-first approach

    Preparation hypothesis, not a confirmed problem: Pressure to build quickly could compete with the posting’s discovery-first approach. Prepare an example of how operator conversations and a process map changed which bottleneck you chose to address.

  • Balancing prototype speed with a reliable handoff

    Preparation hypothesis, not a confirmed problem: A quick low-code demo may show the concept without explaining its workflow or logic well enough for engineers to build from it. Prepare to walk through both a working prototype and the documentation you would hand over.

  • Keeping the backlog focused as tools evolve

    Preparation hypothesis, not a confirmed problem: New agent capabilities may compete for attention with opportunities raised by SEO operators. Prepare a simple way to compare opportunities by the manual effort they address, stakeholder feedback, and whether a useful proof-of-concept is feasible.

03

Practice your answers

Technical practice

How would you map an SEO operator’s current workflow before proposing automation?

What to coverSuggested answer focus: Ask operators to walk through actual tasks, inputs, decisions, handoffs and exceptions, then check the map with them. Explain how you would distinguish a recurring bottleneck from an isolated frustration.

How would you decide whether a manual task is a useful AI automation opportunity?

What to coverSuggested answer focus: Consider frequency, effort saved, consistency of inputs, judgement required and the consequences of errors. Explain when a simpler workflow change or conventional automation would be preferable to an AI agent.

How would you build a working proof-of-concept for a repetitive SEO or GEO workflow?

What to coverSuggested answer focus: Define one narrow task and a demonstrable outcome before choosing no-code, low-code, prompt engineering or lightweight scripting. Show how an operator would review the output and what the prototype would need to prove before handoff.

How would you design and refine a prompt used in a recurring marketing workflow?

What to coverSuggested answer focus: Specify the task, available context, expected output and boundaries, then test the prompt against varied real-world inputs. Explain how you would record failures and revise the prompt without treating a few good examples as sufficient evidence.

When would you use an agent framework rather than a straightforward workflow in a prototype?

What to coverSuggested answer focus: Compare a multi-step agent approach with a more predictable sequence of automation steps, using the task’s decision-making needs and failure modes. The posting names n8n and similar tools as possible approaches, not as mandatory choices.

How would you evaluate whether an MVP actually reduces manual effort?

What to coverSuggested answer focus: Establish the current workflow as a baseline and test the prototype on representative tasks with operator feedback. Consider time saved alongside output quality, required review and failures that could erase the benefit.

What would you document when handing a prototype to product and engineering?

What to coverSuggested answer focus: Describe the current and proposed workflows, inputs and outputs, system logic, decision points and known exceptions. Make clear which behaviours the prototype demonstrates and which requirements still need confirmation for a reliable build.

How would you maintain a prioritised backlog of automation opportunities across the SEO organisation?

What to coverSuggested answer focus: Capture each opportunity’s pain point, affected users, expected value, uncertainty and feedback. Explain how you would revisit priorities when operators’ needs or available AI tools change.

How would you decide whether a newly available AI or workflow tool is worth testing for this team?

What to coverSuggested answer focus: Start with a documented operator problem rather than the novelty of the tool. Suggest a small comparison against the existing approach that examines practical usefulness, reliability and handoff implications.

Behavioural practice

Tell me about a time you uncovered a workflow pain point that was not obvious at first.

What to coverSuggested answer focus: Use a real situation, the conversations and process-mapping actions you took, and the recommendation that resulted. State what you learned from checking your understanding with the people doing the work.

Describe a time stakeholders disagreed about which improvement to prioritise.

What to coverSuggested answer focus: Give the situation, how you gathered and weighed their feedback, and the decision or recommendation you made. Explain the result without claiming consensus if there was none.

Tell me about a time you translated an operational need into something a technical team could act on.

What to coverSuggested answer focus: Describe the original need, how you clarified the workflow and requirements, and how you communicated them. Include the result and any clarification or rework that remained necessary.

Describe a time feedback changed a prototype or proposed solution you were developing.

What to coverSuggested answer focus: Use a real example to explain the initial approach, the feedback you received and what you changed. State the observed result, including any limitations you could not resolve.

02

Sharpen your knowledge

Topics to prepare

  • Discovery before automation

    Posting: Shopee emphasises talking to SEO operators and marketers, mapping current work, and finding pain points before building. Suggested revision: take a hypothetical SEO workflow and list questions that would reveal its steps, manual effort, exceptions, and stakeholder needs.

  • Choosing useful AI-agent opportunities

    Posting: the role identifies where agents or automation could reduce manual effort and scale output for the SEO & GEO team. Suggested revision: compare two hypothetical bottlenecks and explain which, if either, merits a proof-of-concept and what evidence is still needed.

  • Proof-of-concept versus production

    Posting: the Associate builds working MVPs and hands them to a dedicated product and engineering team for production. Suggested revision: define what a small prototype must demonstrate, then separate its assumptions and limitations from production requirements.

  • Backlog prioritisation

    Posting: the role maintains a prioritised SEO automation backlog using team feedback and developments in AI tooling. Suggested revision: rank three hypothetical opportunities and explain how new operator feedback would change the order.

Skills to revise

  • Interviewing and process mapping

    Posting: independent user-insight gathering through conversations and process mapping is required. Suggested exercise: draft five questions for an SEO operator, then turn sample answers into an as-is workflow with bottlenecks and unresolved questions.

  • Building a working automation prototype

    Posting: independent MVP building with no-code, low-code, prompt engineering, agent frameworks, or lightweight scripting is required; familiarity with n8n, Make, or Zapier is a plus. Suggested exercise: build a small illustrative workflow in a suitable stated tool, test its normal path and an exception, and explain what it demonstrates.

  • Using AI tools in a workflow

    Posting: hands-on, day-to-day use of tools such as ChatGPT or Claude is required. Suggested exercise: create and refine a prompt for a hypothetical SEO or content-operations task, checking outputs against sample inputs and recording where human review is needed.

  • Writing a product-and-engineering handoff

    Posting: the role documents workflows, system logic, and requirements so developers can build without repeated clarification. Suggested exercise: write a one-page handoff for the illustrative prototype covering inputs, steps, outputs, exceptions, open questions, and acceptance checks.

04

Your preparation checklist

  • Map a current workflow

    The role starts with understanding how SEO operators and marketers work. Prepare an anonymised process map from relevant experience or a clearly labelled hypothetical example, showing handoffs, manual steps and bottlenecks.

  • Prepare a discovery walkthrough

    Choose an example of stakeholder conversations, if available. Explain the questions asked, how you checked your understanding of the process, and how findings became a recommendation; do not present a hypothetical as past work.

  • Demonstrate a working prototype

    Prepare a short walkthrough of an MVP you built independently using AI tools, prompts, no-code or low-code tools, or lightweight scripting. Show its inputs, outputs, what works, and what still needs validation. If you lack an existing example, build and label a small illustrative prototype.

  • Draft a product-and-engineering handoff

    For the prototype, write a one-page workflow and system-logic brief with inputs, decision points, failure cases and open requirements. The posting emphasizes documentation a development team can use without repeated clarification.

  • Prioritise possible automations

    Create a small illustrative backlog for SEO or GEO work. State the evidence behind each opportunity, expected reduction in manual effort, uncertainties and how stakeholder feedback or new tooling would change its priority.

  • Assemble evidence for the stated requirements

    Prepare concise examples covering relevant digital strategy, product management or digital operations experience; regular use of tools such as ChatGPT or Claude; independent prototyping; and communication across operators, marketers, product and engineering. Keep any pluses, such as n8n or SEO exposure, distinct from requirements.

  • Ask about discovery and handoff

    Prepare questions about which SEO or GEO workflows are most manual today, how operators provide feedback, and what the dedicated product and engineering team needs from a proof-of-concept before taking it toward production.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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