Dedicated AI engineering team.
Offshore AI, LLM, NLP and computer vision engineers work only on your product, as a dedicated AI engineering team. We headhunt and employ them, train them through our Academy and seat them in our offices in Chiang Mai and Bangkok, Thailand. They build with the model providers you already use. You decide what the AI should do for your users.
What you get and what you pay.
Find an AI engineer through offshore staffing or staff augmentation and the hiring is done, but the managing has only started. We do both. Every AI engineer we assign is employed by Azendo and has a desk in our office, training through our Academy and a Talent Success manager, and a service delivery manager stays close to you on delivery.
Price examples
Junior level, full time, everything below included. Mid-level and senior levels are priced in your proposal. All 27 things included ››
- AI engineer From USD 3,100 per month
- LLM engineer From USD 3,100 per month
- NLP engineer From USD 3,100 per month
-
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
-
HR
We are the employer
- Recruitment and technical assessment
- Employment contracts
- Salary and payroll
- Tax and social security
-
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
-
Equipment
We supply the tools
- Laptop and hardware
- Software licences
- LinkedIn Learning access
- Device security and management
One monthly fee per AI engineer, and what it pays for.
You agree a monthly capacity in hours with us. The fee covers the AI engineer's salary and every layer around it: the service delivery manager who oversees delivery, training and development, the workplace, the equipment and the HR behind the employment. It is the same amount every month.
- One agreement and one invoice, with no upfront fee or management surcharge
- Holidays are already priced in, so April and May cost the same
- A capacity report every month, so you see the hours delivered
AI engineers vetted before you meet them.
We headhunt for the models and providers you build with and run every candidate through our assessment first.
- Roles and seniority
- Stack and domain
- Way of working
- Capacity and time to hire
Talk to our teamBook a scoping call - 25 Week 1 Sourcing Headhunted for your brief
- 12 Week 2 AI processing and screening Matched to your stack
- 5 Week 3 Technical testing Pass technical testing
- 1 Week 4 Mindset, culture and logic Proposed to you
Roles on an AI engineering team.
LLM, NLP, computer vision and general AI engineering each have a page. Data engineers and MLOps engineers can join next, with the same service delivery manager.
What a dedicated AI engineering team puts into your product.
Companies hire AI developers when a prototype works in a demo and now has to work for every user, every day. A dedicated AI team takes features from that first version to production: retrieval, evaluation, guardrails, latency and the cost of every request. The AI engineers we assign stay on your product after launch, when quality has to be watched, prompts and models updated, and costs kept in line as usage grows.
- LLM features in your productSearch, assistants, summaries and extraction, built into the software your users already use.
- Retrieval and contextRAG pipelines, embeddings and vector search that give the model the right facts.
- Evaluation setsTest sets and scoring that show whether a change made answers better or worse.
- Guardrails and safetyInput and output checks, fallbacks and human review where the stakes call for it.
- Monitoring and cost controlQuality, latency and spend per request tracked in production.
- Model and vendor changesMoving between models and providers without breaking what users rely on.
Stacks we work in
We hire for your models, providers and stack. What you see here is a sample, not a limit.
- OpenAI
- Anthropic
- LangChain
- Hugging Face
- Google Gemini
- Meta Llama
- LlamaIndex
- Vector databases
- Embeddings
- RAG pipelines
- Pinecone
- pgvector
- Prompt evaluation
- Guardrails
- Observability
- LangSmith
- A/B testing
What a dedicated AI engineering team is.
A dedicated AI engineering team is a group of engineers who build AI features into one company's product, full time: LLM features, search, language processing or computer vision. They use the model providers you choose. You decide what the AI should do, and Azendo manages the engineers and the delivery.
Where it pays off most
It pays off when AI is part of the product roadmap, with features to ship, evaluate and improve with real users. The same engineers stay with your data, your prompts and your evaluations, so each release learns from the one before.
Who is on the team
- AI engineerLLM features inside your product
- LLM engineerPrompting, retrieval and fine-tuning
- NLP engineerClassification, extraction and search
- Computer vision engineerImage and video features
- Service delivery managerOversees delivery on our side and reviews it with you every two weeks
- Talent Success managerFor every specialist: a quarterly development plan and coaching tailored to it
- Your product ownerSets the priorities and accepts the work
Other ways to build an AI engineering team, compared.
| Dedicated team, Azendo | Staff augmentation | Project outsourcing | |
|---|---|---|---|
| What you buy | Agreed monthly capacity from people who work only on your product | A person's hours, billed by the hour or the month | A defined scope, at a fixed price or on time and materials |
| Who manages the team | Azendo, day to day, with you setting the priorities | You do, day to day: Azendo's estimate is four to eight hours a week per specialist | The vendor's project manager |
| Who answers for delivery | Azendo, scored by you every Friday | You do | The vendor, against the agreed scope |
| How long people stay | On your product, and with Azendo for 3.3 years on average | Until the contract ends | Until the project is handed over |
| Best fit | AI features that keep changing as models and users change | A short gap in a team you already run | One project with a clear end |
Try us, at zero risk.
- No deposit
- No upfront fee
- No commitment
We agree a time to hire with you. If we can't find the right people for your team within it, you walk away with no commitment and nothing to pay.
Get in touch"We are 100% committed in a partnership. We go above and beyond, which is why we can say that it is truly a managed service we offer."
Mikkel Schmidt, CEO and founder
Questions about a dedicated AI engineering team.
What does a dedicated AI engineering team do?
A dedicated AI engineering team builds and runs AI features inside your product full time: LLM integrations, retrieval, evaluation, guardrails and monitoring. With Azendo the engineers are ours, managed from Chiang Mai and Bangkok, and they work in your codebase, your accounts and your sprints.
How much does it cost to hire AI engineers this way?
AI, LLM, NLP and computer vision engineers start from USD 3,100 per month at junior level, full time. That monthly figure includes the engineer's delivery management, Talent Success coaching and training, their office and equipment, and HR and payroll. See how the monthly fee is built.
Which models and providers do you work with?
OpenAI, Anthropic, Google Gemini and open models such as Meta Llama, with LangChain, LlamaIndex, Hugging Face and vector databases such as Pinecone or pgvector. The engineers work with the providers and contracts you already have, and they can compare models on your own evaluation set before you switch.
Does our data leave our environment?
The engineers work inside your accounts and with your model contracts, so your data follows the agreements you already have with those providers. Access is set by you and can be revoked at any time, and nothing runs through accounts of ours.
How do you know an AI feature works?
With evaluation sets built from real examples. Every change to a prompt, a model or the retrieval is scored against them before it ships, and quality, latency and cost are tracked once it is live.
What is the line between AI engineering and AI automation?
AI engineering builds features into the product your customers use. AI automation applies the same tools to your internal processes. A dedicated AI automation team can join under the same agreement when you need both. For a one-off build delivered as a project, our AI development services are the better fit.
Are the engineers trained in AI?
Yes. Every team member is AI trained through our Talent Success and Academy programme. Each AI engineer also has a Talent Success Manager and a development plan with skill goals, rebuilt every quarter with coaching in between, so their skills follow the models and tools your product needs next.
Do the AI engineers work remotely?
Yes. We employ them and assign each one to your product full time. They work in your repositories and the model provider accounts you already have, from our Chiang Mai and Bangkok offices or, up to two days a week, from home over a secure VPN. You reach them directly, usually on Slack or Teams.
Service areas you can add to an AI engineering team.
Each role joins under the same agreement, works in the same sprints and reports to the same service delivery manager. You add one when your product calls for it.
AI engineering team AI Engineer, LLM Engineer, NLP Engineer, Computer Vision Engineer. The core of the team. On the team 
Data science Analysis, models and evaluation Add to the team → 
AI automation engineering Agent workflows and internal automation Add to the team → 
MLOps engineering Deploying and monitoring models in production Add to the team → 
Data engineering Pipelines, warehouses and reporting models Add to the team → Let's scope your AI engineering team.
Thirty minutes with a service delivery manager. You leave with a clear picture of the team you would need, what it would deliver and how we would hire it in four weeks.
- No deposit and no upfront fee
- No commitment until the right people are on your team
- If we can't find them inside the agreed window, you walk away at no cost
Mikkel Schmidt and John Mark, the people you would talk to. No slides, no sales script. Loading the form…
We reply within one business day.
