Dedicated AI engineering team.
AI, LLM, NLP and computer vision engineers work only on your product, as a dedicated AI engineering team. Azendo employs, trains and manages them from its own 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.
With offshore staffing or staff augmentation, the provider finds an AI engineer and the managing is left to you. We do it as a full service. The AI engineers are ours: we employ them, assign them to you full time, give them an office and equipment, train and coach them, and run delivery with you every week.
Price examples
Mid-level, full time, everything below included. Junior and senior levels are priced in your proposal. All 27 things included ››
- AI engineer From USD 4,200 per month
- LLM engineer From USD 4,200 per month
- NLP engineer From USD 4,300 per month
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Service
We manage and develop the team
- A service delivery manager who runs the team and answers for 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 specialist
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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 own 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
One monthly fee. Everything around the AI engineer is in it.
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 runs the team, 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
- Capacity moves up or down at the next monthly cycle
Your AI engineering team, tailored down to every detail.
We select every person for your stack, your product and the way your team works. When the right AI engineers are not already with us, we headhunt them and test them ourselves before you meet them.
- Roles and seniority
- Stack and domain
- Way of working
- Capacity and start date
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
Any role your roadmap needs.
These four are the AI engineering roles with their own pages. Beyond them we assign specialists across eleven disciplines, on the same agreement and with the same service delivery manager.
What a dedicated AI engineering team works on.
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
- 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
Matched to what you run today, agreed at scoping.
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 managerRuns the team on our side and answers for delivery
- Talent Success managerFor every specialist: a development plan and coaching every month
- 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 work | A service delivery manager, 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, every week | 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 | A product that keeps growing, with a roadmap that runs for years | 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 don't hand you an AI engineer and step back. We build the team around your product, and we stay in it every week."
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 and computer vision engineers start from USD 4,200 per month, and NLP engineers from USD 4,300, at mid-level and full time. The fee covers the engineer and everything around them: delivery management, a Talent Success Manager and training, the office and equipment, 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 both are on the roadmap.
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, reviewed with coaching every month, so their skills follow the models and tools your roadmap needs next.
Disciplines that join an AI engineering team.
Each discipline joins under the same agreement, works in the same sprints and reports to the same service delivery manager. You add one at the next monthly cycle, when the roadmap 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 when it could start.
- 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
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