Dedicated AI engineers for your offshore team.
Offshore AI engineers in Chiang Mai and Bangkok, working full time on your product and managed by us. An AI engineer builds model-backed features into software that already has users, and keeps them reliable in production.
We employ, manage and keep training the engineers we assign, and you pay one fixed monthly fee.
This role is part of a dedicated AI engineering team. It's staff augmentation, fully managed: take one role on its own, or the whole area as one delivery team.
One AI Engineer, assigned to your product and fully managed.
We assign an AI Engineer to your team full time and run everything around them: a service delivery manager who oversees delivery, training and coaching, the office and equipment, and HR and payroll. The price below is for a junior AI Engineer; other levels are priced in your proposal, and how the monthly fee is built explains the arithmetic.
From price
One junior AI Engineer, full time, everything below included. All 27 things included ››
- AI engineer From USD 3,100 per month
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Service
We manage and develop the team
- A service delivery manager who oversees operations and delivery
- A 1:1 with our Head of Delivery every two weeks
- Weekly delivery scoring and monthly capacity reports
- A Talent Success Manager for every team member
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HR
We are the employer
- Recruitment and technical assessment
- Employment contracts
- Salary and payroll
- Tax and social security
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Facilitation
We provide the workplace
- A desk in our office in Chiang Mai or Bangkok
- A Workplace Experience Manager on site
- Team events through the year
- IT support
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Equipment
We supply the tools
- Laptop and hardware
- Software licences
- LinkedIn Learning access
- Device security and management
What an AI Engineer does on a dedicated AI engineering team.
They work in your codebase with your product and engineering team, ship AI features behind flags and report on cost, latency and quality every week.
AI Engineer skills and technologies
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Integrating language models into existing products, with retrieval, structured output and tool use.
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Building evaluation sets so a prompt change can be measured rather than guessed at.
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Monitoring cost, latency and output quality after launch, when AI features tend to degrade quietly.
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Building the fallback path for when a model provider is slow or unavailable, so the product keeps working in a reduced form.
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Red-teaming prompts against injection and jailbreak attempts before a feature reaches users.
AI Engineer seniority levels.
Junior to senior. Production AI work rewards engineers who have shipped and run AI features before. That track record comes with the higher levels, and the level is part of how the monthly fee is built.
When your team needs an AI Engineer.
The most common AI role, working on products already in production. Often paired with an LLM or NLP engineer in a dedicated AI team. Companies that hire remote developers for AI work usually start with this role, because it ships features into the product users already have.
What we look for in a dedicated AI Engineer.
We look for AI engineers who measure before they tune. They should build an evaluation set before changing a prompt and understand retrieval as well as generation. They should also plan the fallback for when a model provider is slow.
A remote AI Engineer's first three months on your team.
- Weeks 1 to 2Reviewing the use case, data and any existing AI features, and building a first evaluation set.
- Weeks 3 to 6Shipping the first model-backed feature behind a flag, with cost and quality monitored.
- Months 2 to 3Owning the feature in production, improving quality against the evaluation set.
Questions about adding an AI Engineer to your team.
Can you work with our existing AI feature?
Yes, and a large part of our AI work is exactly that: adding evaluation, monitoring and cost controls to a feature already live. The engineer starts by measuring how the feature behaves today. Retrieval, prompts or models are then improved with evidence, so quality goes up without surprises for your users.
Which model provider do you recommend?
Whichever fits your constraints on quality, cost, latency and where your data may go. Everything is built so switching provider later is straightforward, with an evaluation set to compare models fairly. Model providers change prices and retire models often, so keeping that option open protects your product.
Add remote AI engineers to your team.
Tell us the feature you have in mind or the one already live, the data behind it and the model provider you use. We'll come back with the AI engineer profile we'd hire and the fixed monthly fee. The hire is done in four weeks from signing.
Tell us what your AI engineer would work on.
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