How to Hire AI Developers in the Philippines: What to Test Before You Sign
Hiring AI developers is harder than hiring developers, for a plain reason: the title covers several different jobs, and most interviews cannot tell them apart. A candidate can speak fluently about models, agents and prompts and still struggle to ship a feature into a real system. Another can be an excellent engineer who has simply never worked with AI. Philippine teams are a popular choice for global companies that want strong engineers in a convenient time zone, but the market is no different on this point: you need to know what you are hiring, and you need to test it.
This guide covers which profile you actually need, the practical tests that reveal skill, how the hiring route changes what you manage, and what to settle before you sign. If you are choosing a partner instead of individual developers, our due-diligence checklist for hiring an AI software development partner is the companion piece.
"Hire" can mean three things here: employing developers directly in the Philippines, engaging freelancers, or having a partner place a dedicated team that works as an extension of yours. This guide is for any of them. The tests in Step 2 apply whichever route you choose, and Step 3 explains what each route makes you manage.
Step 1: Decide Which "AI Developer" You Need
Three profiles get called the same thing:
The machine learning engineer trains, tunes and evaluates models. They work with data, metrics and experiments. You need this person when the model itself is the product, or when off-the-shelf models are not good enough for your data.
The AI application developer builds software that uses models: calling them, handling their answers, combining them with business rules, and connecting the result to your systems. Most enterprise projects, such as document extraction, chatbots, identity verification or natural-language queries, need this profile.
The AI-native software engineer builds ordinary software using AI tools throughout: writing specifications, reviewing generated code, testing it. They are often the largest part of a team, and the skill that sets them apart is judgment about AI output, not model knowledge. We describe this shift in how the developer's job is changing.
Write down which of the three your project needs, and in what proportion. Many projects need one machine learning engineer or none, a few application developers, and several AI-native engineers. Asking for "AI developers" without that breakdown invites resumes that all look alike.
Step 2: Test the Work, Not the Vocabulary
An interview tests how well someone explains. A work test shows what they do. Use both, and weight the second heavily. Keep the test realistic, paid where the law and your policy allow it, and short enough that good candidates will do it.
Review AI-generated code.
Give the candidate a small module generated by an AI tool, with a few planted problems: a missing edge case, an insecure input, a function that works but cannot be maintained. Ask them to review it as they would a colleague's pull request. Strong developers find the real issues and explain the trade-offs. Weak ones approve it or rewrite everything. Our post on code review when half the code is AI-generated describes what good looks like.
Turn a vague request into a specification.
Give them two paragraphs of business need and ask for the questions they would ask and a first-draft specification with acceptance criteria. This reveals whether they think about the problem or jump to code. It is the core skill in spec-driven development.
Build a small feature with AI tools.
Let them use whichever tools they normally use. Watch for how they direct the tool, how they check its output, and whether they can explain what was generated. The tool matters less than the discipline.
Test an AI feature.
AI output varies from run to run, so ordinary unit tests are not enough. Ask how they would check that a document-reading step is accurate, what they would do with low-confidence answers, and what happens when the model is unavailable. Good answers mention evaluation sets, thresholds, a human review path and a fallback.
Handle data and security.
Ask what they would not paste into an AI tool, how they would treat personal data in a prompt, and how they would keep secrets out of generated code. For regulated data, this matters as much as technical skill.
Explain a failure.
Ask about a project where AI-assisted work went wrong, and what they changed afterward. Candidates who have shipped real AI features have these stories. Candidates who have only experimented often do not.
Score every candidate against the same simple rubric, with the same reviewer, so results are comparable.
Step 3: Know What Each Hiring Route Makes You Manage
The route you choose changes who handles what.
Hiring directly gives you full control and full responsibility: sourcing, contracts, equipment, payroll, compliance, replacement if someone leaves, and day-to-day management.
Freelancers are fast to start and flexible, but continuity, quality control and knowledge transfer rest with you.
A dedicated team through a partner places engineers who work as an extension of your own team while the partner handles employment, retention, equipment and replacement. This is how BlastAsia's dedicated developer teams work, and it suits ongoing, evolving work. Our xDD engagement model is built for it.
A fixed-scope build moves the delivery to a partner entirely and suits a bounded project with a defined outcome. Our comparison of xDD and Turnkey covers when each fits.
If you are unsure, ask which parts of the work you want to manage yourself. Teams that want to direct the engineers daily choose a dedicated team. Teams that want an outcome and a handover choose a fixed scope.
Step 4: Settle These Before You Sign
Intellectual property.
The contract should say plainly that the code, the specifications and the work product belong to you.
Tools and data.
Agree which AI tools may be used, what data may enter them, and where that data goes. Ask whether the environment is isolated so your inputs are not used to train anyone else's model.
Continuity.
What happens if a developer leaves, takes leave or underperforms? How quickly is a replacement found, and who transfers the knowledge?
Overlap and communication.
The Philippines sits at UTC+8, which gives a comfortable daytime overlap with much of Asia and Australia, and partial overlap with Europe and the United States. Agree on overlap hours, reporting rhythm and how decisions are recorded.
Quality gates.
Agree how work is reviewed and accepted before it reaches you: code review, automated checks and acceptance criteria.
Exit.
Make sure you could hand the work to another team without losing access to code, documentation or specifications.
Red Flags
A candidate who cannot say what an AI tool got wrong for them. Portfolios that show demos but not production systems. Reluctance to take a practical test. Vague answers on data handling. A team presented as "AI-native" with no one named to review the generated code. And, on the partner side, anyone who cannot answer the questions in our due-diligence checklist.
A Short Checklist to Take Into Your Next Interview
Which of the three profiles do we need, and how many of each? Which work tests will we run, and who scores them? Which hiring route fits how much we want to manage? Who owns the code, and what tools and data are allowed? What is the plan if someone leaves? If those answers are clear, you are ready to interview well.
If you are planning to hire AI developers in the Philippines and want help structuring the team or the tests, tell us what you need to build and we'll help you shape the team.
About BlastAsia: BlastAsia is a Philippines-based software company that builds AI-powered software for enterprises worldwide, whether it's a new application or AI layered on the systems you already run. We build it AI-natively: specifications first, with code generated and reviewed on the Xamun Software Factory, so delivery is faster and more predictable. Engage us as a dedicated team (xDD) or as a fixed-scope Turnkey build, and you own what gets built.
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