AI Solution Specialist

A promising AI use case can stall between the client workshop and the engineering handoff: unclear data, an optimistic demo, or a brief that cannot be built. This role sits at that junction—helping clients define the problem, showing a credible direction, and working with engineers to shape the next step.

1. About the role

You will be the client-facing link between business stakeholders and an internal AI engineering team. Turn AI opportunities into scoped, delivery-ready solution directions: lead discovery, explain the technology without overclaiming, document what the client needs, and partner with architects and engineers through pre-sales and early proof-of-concept work. Engineering colleagues collaborate on prototypes and technical delivery; your distinctive contribution is the clarity of the client-to-delivery bridge.

2. What you'll own

• Discover use cases that can be measured. Lead stakeholder conversations, clarify the underlying business problem, and scope AI opportunities around practical outcomes.
• Make the solution understandable. Deliver presentations, demos, and walkthroughs suited to each client's context and level of AI familiarity; explain technical options to both business and engineering audiences without overselling.
• Create the handoff. Write requirements and scoped briefs that the delivery team can act on, including use case summaries, proposals, and capability documentation as needed.
• Shape early solution work. Collaborate with AI engineers and architects in pre-sales, solution design, and PoC planning. Join prototype reviews and client demos, translating feedback between technical and client teams.
• Surface delivery risks early. Flag data readiness, integration constraints and mismatched expectations before they become promises the team cannot keep.
• Represent and improve the AI practice. Join client briefings, industry events and internal showcases; capture reusable use cases, solution patterns and engagement insights for the capability catalogue. Track AI developments and share relevant updates with colleagues.

3. What we're looking for

Must-have

• A bachelor's degree, preferably in Computer Science, IT, or a related field.
• 3–5 years in client-facing or cross-functional work such as Business Analysis, Product Ownership, Project Management, AI Engineering, or AI Solution Architecture, with hands-on involvement in AI projects—agents, solution design, engineering, or implementation. Familiarity with AI in theory alone is not the same as project experience.
• Experience working alongside technical teams on solution design or delivery, with enough architectural understanding to speak credibly to clients and engineers.
• Working knowledge of AI/ML, large language models, retrieval-augmented generation and agentic systems; familiarity with at least one of AWS, Azure or GCP in an AI-services context.
• Evidence of presentations and storytelling for technical and non-technical audiences; ability to turn ambiguous client problems into a clear scope and write proposals, use case summaries or capability documents.
• Organized, proactive management of several client engagements, consultative listening and clear communication across engineers, architects and business stakeholders. Fluent English is required.

Nice-to-have

• Exposure to Azure OpenAI, AWS Bedrock or similar AI platforms; RFPs, capability decks or client-facing solution documents.
• Projects in government, finance, logistics or manufacturing; AI or digital-transformation work on the client or consulting side.
• The role is based in HCMC, and applicants need to be available for an offline technical interview. Working hours are listed above; flexible hours and working from home depend on project arrangements. The role calls for a persuasive presenter who can also say when the data or integration is not ready.

4. Why this move

For a BA, consultant or technical PM already involved in AI delivery, the appeal is a wider stretch of the same problem: from first client conversation to the brief, demo and engineering review. An engineer drawn to this role would need to enjoy stakeholder discovery as much as solution design. This is a client-facing bridge, not a promise of sole ownership over the engineering build.

5. Why Work here

The work brings client discovery, AI solution shaping, and engineering collaboration into one remit. The hiring group's broader technology and engineering portfolio gives context to the problems the team may encounter, while the actual projects and scope of this position remain those described above.

• Gross salary is negotiable (competitive. 100% salary during probation applies.
• A performance bonus is variable and assessed annually based on business and individual performance; the 13th-month payment is not fixed. A possible one-to-three-month equivalent depends on business and individual performance.
• Meal allowance and transportation allowance are listed, with amounts unspecified.
• Full social insurance applies, with contributions on the total gross base salary. Additional private insurance from probation is listed.

A work laptop or desktop is provided for work.

• Flexible working hours are listed alongside standard office hours; a project-dependent work-from-home policy applies according to project arrangements.
• Training during probation and access to LinkedIn e-learning courses support continued learning.
• Annual salary review and annual performance review are listed separately, together with periodic company gatherings and events.

6. Interview process

• HR meeting — online.
• Technical interview — offline in HCMC.

Questions worth asking

• Which AI use cases are currently moving from discovery into PoC, and where do they most often stall—data access, integration, or stakeholder expectations?
• Evidence of presentations and storytelling for technical and non-technical audiences; ability to turn ambiguous client problems into a clear scope and write proposals, use case summaries or capability documents.
• Organized, proactive management of several client engagements, consultative listening and clear communication across engineers, architects and business stakeholders. Fluent English is required.

7. How to apply

Apply through LinkedIn, or send your CV directly to the headhunter by DM/direct message if you prefer to discuss your AI project and client-facing scope first.

8.. About the company

The hiring group is a Singapore-headquartered technology and engineering organization working across aerospace, urban solutions, defence and public security. Its operations span multiple regions, serving commercial and public-sector customers. This HCMC opening is a client-facing AI solution role within that broader engineering context.