Hire An AI Developer · UK & Europe
Outsource LLM Application Development for Your UK Team
Hire a dedicated Philippine LLM developer who works your UK or European business hours. Define the workflow, evidence and ownership terms before the build.
Junior profiles from £1,140 / €1,320

Should you outsource LLM application development?
For UK and European employers with a continuing product backlog, a dedicated Philippine AI developer can be a suitable way to outsource LLM application development. The standard all-inclusive client fee starts at [£1,330 / €1,540 per month ($1,750)](/pricing). Keep product decisions and acceptance testing with your team, and agree code ownership in writing.
What does outsourcing an LLM application actually mean?
Outsourcing an LLM application means assigning development and maintenance to external talent while your company directs the product, data access and priorities. You can build around your own workflows: retrieval over internal documents, structured data extraction, customer-support assistance, product copilots or agents that call approved business systems. Agree responsibility for architecture, review and release decisions before commissioning the work.
How Borderless Recruit helps: it supplies dedicated full-time AI developers from the Philippines who work only for your company during your UK or European business hours. Borderless Recruit handles sourcing, vetting, local employment contracts, payroll and HR for a flat monthly fee. You manage the application backlog and acceptance decisions.
Which LLM applications suit a dedicated developer?
Consider a dedicated developer when your application needs continuing integration work, evaluation and maintenance. Start with a defined workflow and an accountable business owner. Use the examples below as suggested acceptance criteria, then adapt them to the consequences of an incorrect answer or action.
Suggested use cases and acceptance criteria
| Use case | What the developer builds | Acceptance test to request |
|---|---|---|
| Knowledge assistant | Retrieval-augmented generation (RAG): answers grounded in retrieved company documents | Answers cite supporting passages; missing evidence triggers a controlled no-answer response; restricted documents stay inaccessible |
| Document workflow | Extraction, validation and routing into your CRM or operations system | Malformed or incomplete documents enter a review queue; retrying a request does not create duplicate records |
| Product copilot | An LLM feature inside your existing application, with authentication and API integration | Actions respect the user's permissions; failed API calls produce a recoverable error |
| Tool-using agent | Approved tools, state handling and human confirmation | Sensitive actions require approval; an instruction hidden in retrieved content cannot authorise an action |
If the main challenge is connecting models to an established software stack, use the brief for an AI developer for API integration to clarify the systems, permissions and failure paths involved.
Should you use prompting, RAG or fine-tuning?
Ask candidates to justify the simplest approach that meets your acceptance criteria. Treat the following as a commissioning sequence, rather than a requirement to use every technique:
- Start with prompting for instructions, output structure and clearly defined behaviour. Establish examples of acceptable and unacceptable responses before adding complexity.
- Consider RAG when answers need private or changing knowledge. Require the developer to explain document access, retrieval failures, citations and how updates or deletions reach the application.
- Consider fine-tuning for repeatable specialist behaviour when you have suitable training data and a separate evaluation set. Ask what measured failure it addresses and why simpler changes are insufficient.
- Keep deterministic business rules in conventional software where appropriate. Require explicit validation before generated output updates a business record or triggers an action.
Test a developer with a realistic retrieval task
A useful assessment asks the developer to build and explain a small system, rather than answer trivia about model APIs. Illustrative task: provide synthetic policy documents containing conflicting versions, a withdrawn policy and an instruction embedded in a document telling the assistant to ignore its rules. Give test users different document permissions. Request a retrieval application with citations, an API endpoint and documented failure behaviour.
- Retrieval and permissions: ask the same question as users with different access rights. Check the retrieved passages as well as the final answer; hiding a citation is not an access control.
- Evaluation: include answerable, unsupported and ambiguous questions. Ask the candidate to record expected behaviour and explain failures, including responses to the malicious document instruction.
- Engineering: request readable code, configuration outside source files, tests and a reproducible setup. A reviewer should be able to run the application from its documentation.
- Reliability: simulate a provider timeout or rate limit. Inspect retries, error messages and logs, and check that logs do not expose sensitive document content.
- Judgement: ask what the candidate would change before production, what remains uncertain and which actions should require human approval.
Have a technical reviewer reproduce the submission and inspect its weaknesses. A polished demonstration alone does not establish readiness. This exercise should inform your hiring decision; it is not proof that the finished application will handle every failure.
Set the data and ownership boundaries before access
Document the employment arrangement, contracting parties and data flows before granting access. Overseas access to personal data can be a restricted transfer under UK GDPR; whether the recipient is a separate legal entity matters. Assess your arrangement using the ICO's international-transfer guidance. EU organisations should assess transfers outside the EU using the European Commission's data-protection guidance. A staffing arrangement does not itself establish compliance.
- Agree ownership and permitted use of source code, prompts, evaluation sets and documentation in writing. Identify pre-existing and third-party components that cannot be assigned to your company.
- Use company-controlled repositories, cloud accounts and model-provider accounts. Grant access by task and environment, with separate production approval and a documented offboarding process.
- Record which data reaches each model provider, its retention settings and whether submitted data may be used for training. Use synthetic assessment data and restrict production data access.
- Maintain a licence inventory for models, libraries and reused code so commercial restrictions are visible.
Define what your team must be able to operate
Before accepting a pilot, ask for the repository, deployment instructions, evaluation results, known limitations and a runbook covering provider outages, retrieval failures and rollback. Your internal owner should be able to locate these without relying on the developer's personal accounts or memory.
Make release approval depend on observable behaviour: authorised users can complete the target workflow, unsupported requests take the agreed fallback path, and failures reach a named operator. Record unresolved defects and decide which prevent launch. Re-run the agreed evaluation when prompts, retrieval settings or model versions change.
Ask the developer to separate the staffing fee from application operating costs in the budget: model usage, hosting, document processing and monitoring. Confirm who pays each supplier and how spending alerts and usage limits will work. Avoid treating the recruitment price as the complete cost of running the product.
The developer's Philippine shift overlaps your UK or European business hours. The Philippines does not observe daylight saving, so confirm shift adjustments when your local clocks change. Name an internal product owner, record architecture decisions and reserve backlog capacity for maintenance. A dedicated developer versus freelancer comparison can help you decide how much ongoing capacity the application needs.
Sources
- ICO's international-transfer guidance — ico.org.uk
- European Commission's data-protection guidance — commission.europa.eu
Hiring Locally vs Borderless Recruit
Monthly employer cost of a comparable local hire — gross salary plus statutory employer costs — against our flat monthly fee. Planning figures from the sources below, not a guaranteed saving.
| Hiring in the UK | Hiring in the Netherlands | Borderless Recruit | |
|---|---|---|---|
| Monthly cost | £5,990–£9,670 | €5,700–€9,120 | from £1,330 · €1,540 · $1,750 |
| Junior profiles | — | — | from £1,140 · €1,320 · $1,500 |
| Employer costs | +16% on top of gross (employer NI and minimum pension) | +17% on top of gross (employer premiums and health levy) | None — one flat monthly fee |
| Time to hire | Depends on your hiring process | Depends on your hiring process | 10–14 business days |
| If it doesn't work out | Re-recruitment is on you | Re-recruitment is on you | Free replacement + refund for days not worked |
| Estimated annual difference | £78,000 | €70,440 | vs. the midpoint (or median) of each local figure |
Sources: United Kingdom: ITJobsWatch — AI Engineer (UK permanent job ads, 25th–75th percentile, “AI Engineer”, 6 months to September 2026); Netherlands: CBS StatLine 86355NED — hourly wages by occupation (2025, provisional) (2025 provisional, 25th–75th percentile, software and application developers; hourly pay × 39 h × 52 weeks incl. 8% holiday allowance). Employer costs use the statutory rates on our pricing page.
Calculate Your Savings
Enter the salary you would pay locally in the UK or the Netherlands — and see how much stays in your business.
How much would you save on an ai developer? Set the salary you would pay locally.
Local employer cost = gross salary plus 16% statutory employer costs in the UK (employer NI and minimum pension; equipment and office costs not included). Salary guide: ITJobsWatch — AI Engineer. The Borderless Recruit figure is the standard monthly fee for an ai developer with no additional employer costs.
- Local employer cost
- £7,830 /month
- With Borderless Recruit
- £1,330 /month
- Monthly savings
- £6,500
How We Know Our AI developers Are Good
To enter our database, every candidate passes three assessments and an in-depth interview — only a small fraction of applicants ever reach your shortlist.
Live English Interview
Fluent written and spoken communication, tested in a live interview — not a questionnaire.
Personality Assessment
Commitment, reliability and the ability to work independently and remotely, long-term.
Professional Skills Test
A hands-on test in the tools and real tasks of a ai developer — not just a resume.
Our Process
What You Can Expect From Working With Us
Free consultation with one of our representatives in Borderless Recruit - full characterization of the role for the business and the specific requirements from the employee
Search for an employee from our pool of talented employees to suit the specific needs of the business
A job interview with the employer with the 2-3 final candidates we provide from the database
Starting the employment of a talented and hardworking employee
Frequently Asked Questions
Is it better to hire an LLM engineer or outsource the whole project?+
A dedicated engineer suits a continuing backlog when you have product ownership and access to technical review. An agency may suit a bounded assignment where discovery, architecture and delivery management must be included. Confirm those responsibilities in the proposal; the supplier label alone does not settle them.
Can outsourced LLM development comply with UK GDPR?+
It can, but the specific contracts, access arrangements and data flows need assessment. Remote access can engage international-transfer rules; check the [ICO's guidance](https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/international-transfers/) and document the applicable mechanism where required. Also review model-provider processing and security controls.
Who maintains an outsourced LLM application after deployment?+
Name the maintainer before development starts. Agree responsibility for evaluations, model changes, document updates, integrations and incidents. Define support coverage and escalation separately from ordinary business-hour collaboration, and confirm what happens when the developer is unavailable.
How long does an outsourced LLM application take to build?+
The schedule depends on data readiness, integrations, security review and the required reliability. Ask for milestones tied to a working evaluation set, an integrated pilot and production acceptance. A recruitment timeline is not an application delivery estimate.
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