AI Solution Engineer

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Location: Ho Chi Minh City, Vietnam
Employment type: Full-Time, Permanent
Function: Customer Enablement (CE)
Experience: 3-5 years
Reports to: Customer Enablement Leadership
The Opportunity
Customer Enablement runs on data and on tooling. Our support, retention and operations teams need reporting, dashboards and automation to do their jobs - and because modern AI tooling makes building things fast, a good deal of it has been built locally, by the people who needed it, in an afternoon.
Much of it is genuinely useful. The problem is that it is not built to last: data is loaded by hand, nothing is scheduled, failures are silent, there is no documentation, and when the person who built it is on leave, it stops working. Your job is to take that work on and make it real engineering - automated, monitored, documented, properly hosted, and owned by the function rather than by an individual. Then to build what comes next that way from the start.
This is a hands-on software engineering role, and it is a broad one. You will work across the systems CE depends on - CRM, collaboration tools, data warehousing and reporting - building the integrations that remove manual steps, and using modern AI tooling such as Claude and Microsoft Copilot as part of how you build. You will own what you deliver end to end, from requirement through to running it in production, and you will work directly with the people who use it.
To be clear about the kind of AI work this is: this is applied engineering, not machine learning research or model development. You will be building software that uses AI tooling and LLM APIs to solve practical problems for our support, retention and operations teams - integrations, automation, agents and internal applications - rather than training or tuning models.
We are looking for solid software engineering fundamentals first. Experience with LLM APIs, AI-assisted development or the Salesforce platform is welcome and will help you move faster, and this role gives you the scope to build on it.
Key Responsibilities
Making Existing Tooling Production-Ready
• Take ownership of locally-built reports, dashboards and automations, working with the people who built them to understand what the tool needs to do and what matters about it.
• Replace manual steps with scheduled, automated processes so that nothing depends on a particular person being available.
• Add the engineering that is usually missing - error handling, logging, alerting on failure, managed credentials, proper hosting and access control.
• Document what you take on, so that it can be supported by someone other than its author.
Integration & Data
• Build and maintain integrations with the systems CE relies on, including CRM, Microsoft 365, Atlassian tooling, and our data warehousing and reporting platforms.
• Work with REST APIs and authenticated services, handling pagination, rate limits, retries and partial failure sensibly.
• Write reliable data pipelines - extracting, transforming and loading data on a schedule rather than on request.
• Keep data handling consistent with Keyloop's security and compliance requirements.
Building with AI Tooling
• Use AI tooling - principally Claude, alongside Microsoft Copilot - as part of how you build, and apply it where it delivers real efficiency for CE.
• Build integrations and small applications that use LLM APIs, with sensible attention to cost, reliability and whether the output is actually correct.
• Develop enough familiarity with Keyloop's internal support platform and its tooling to work alongside it and to assess what others have built on it.
Engineering Standards
• Establish sensible defaults for how CE tooling is built, hosted, scheduled and documented, so that each new thing is cheaper to build and easier to support than the last.
• Review and give an honest technical assessment of tooling built elsewhere in the function - what it does well, what it would take to support properly, and whether it duplicates something that already exists.
• Use version control, testing and repeatable deployment as a matter of course.
Collaboration
• Work directly with CE stakeholders - across Support, Retention, Operations and Knowledge & Education - to understand what they need and keep them informed.
• Explain technical reality in plain business language, including when the answer is that something will take longer or should not be built.
• Liaise with Keyloop's wider Technology, IT and AI Centre of Excellence teams where your work touches theirs.