AI staff augmentation: add AI engineers to the team you already run
Add named AI engineers to your own team, under your direction, for the hours you need. Webify.AI employs them, replaces them if needed and assigns the IP in their code to you.
You direct the work
Engineers join your stand-ups, tools and repositories.
Hourly or monthly
From $45 an hour for an AI / LLM engineer, from 80 hours a month.
Free replacement
Within five working days, with a handover overlap.
What is AI staff augmentation?
AI staff augmentation means adding outside AI engineers to your own team for as long as you need them. You set the priorities and manage the work day to day. The provider employs the engineers, pays them and replaces them if needed. You buy capacity and skills, not a finished project.
The engineers work inside your process. They join your stand-ups, use your ticketing and chat tools, and commit to your repositories. Day to day, they work like members of your team who happen to be based in India.
AI staff augmentation differs from general staff augmentation in one way: the skills are newer and harder to judge. A hiring manager can usually assess a web developer from experience. Assessing an AI engineer is harder when nobody on the team has built an AI system before. That makes the interview and the trial matter more.
AI staff augmentation suits work such as:
- Adding a first AI feature to a product before you hire a full-time AI specialist.
- Moving an AI prototype into production, with evaluation and monitoring.
- Covering AI skills while you recruit permanent staff.
- Running a fixed period of AI experiments before deciding what to build.
- Giving an existing AI team extra capacity for a launch.
What is the difference between staff augmentation and outsourcing?
With staff augmentation, you direct named engineers who work inside your team, and you own the decisions. With outsourcing, you hand a defined project to a provider, who directs its own people and delivers a result. Augmentation suits changing AI work; outsourcing suits a fixed scope you would rather not manage.
| AI staff augmentation | AI project outsourcing | |
|---|---|---|
| Who decides the architecture | Your team, with the engineers' advice | The provider, within the agreed scope |
| Who understands the system afterwards | Your team, because the work happened inside it | Mostly the provider, unless handover is written into the contract |
| When requirements change | You change the priorities the next morning | A change request, often with a new price |
| How you pay | Per hour or per month, for the engineer's time | A fixed price or milestones, for the result |
| Who carries delivery risk | You, because you direct the work | The provider, for the agreed scope |
| What you need in-house | Someone to set priorities and review the work | Someone to write the scope and accept the result |
| Best fit for AI work | AI features that improve through many small changes | A contained AI build with clear acceptance tests |
AI work often suits augmentation, because requirements shift once real users try the system. A scope written before anyone has tested a model on your data tends to be wrong in places. Outsourcing still works well when you can define success with a test set up front.
Webify.AI offers both. This page covers augmentation. If you have a fixed-scope AI project, ask about project delivery through our contact page.
Our rates
Published prices in US dollars. Monthly plans are 160 hours, about 15% below the hourly rate.
Mid-level developer
3 to 5 years
$25 / hour
$3,400 a month (160 h)
Senior developer
6 or more years
$35 / hour
$4,750 a month (160 h)
AI / LLM engineer
Agents, RAG, IBM watsonx
$45 / hour
$6,100 a month (160 h)
Senior AI engineer
Leads AI architecture and delivery
$60 / hour
$8,150 a month (160 h)
Two-week trial with the developer you choose. No charge if you stop within the first five working days. US Eastern clients get 09:00 to 12:00 US Eastern time through an evening shift, at 15% extra. Full pricing and comparisons.
Should I build an in-house AI team or outsource?
Build in-house when AI will be core to your product for years and you can recruit and keep AI engineers. Augment or outsource when you need AI skills now, the workload is uncertain, or you want to test an idea first. A mix also works: a small in-house core plus augmented engineers.
Swipe the table sideways to see every column.
| In-house AI team | AI staff augmentation | AI project outsourcing | |
|---|---|---|---|
| Time to start | Months: recruiting and notice periods | Days: two named profiles within 48 hours | Weeks: scoping and a proposal |
| Cost basis | Salary, benefits, recruiting fees and equipment | Hourly or monthly, from $45 an hour for an AI / LLM engineer | Fixed price or milestones |
| Commitment | Permanent employment | Hours you can change from month to month | The project scope |
| Who directs the work | You | You | The provider |
| Knowledge stays with | Your company | Your team and your repositories | The provider, unless handed over |
| If someone leaves | You recruit again | Free replacement within five working days | The provider deals with it |
| Best for | Long-term core AI capability | Ongoing AI work with changing priorities | A defined AI project with clear acceptance tests |
Cost is part of the picture. KORE1's 2026 rate guide lists US staffing-agency rates for AI / ML engineers at $140 to $240 an hour. IT Jobs Watch puts the UK median for a contract software developer at £525 a day in October 2026. Those figures help you compare, but time and commitment usually decide it.
Questions that usually settle the choice:
- Will AI be part of your product in three years, or is this one feature?
- Can you hire and keep AI engineers where you are, at the salary the market asks?
- Does anyone on your team know enough to direct AI engineers?
- How soon does the first AI feature need to ship?
If nobody in-house can direct AI work yet, start with a senior AI engineer who can lead it.
What do AI staff augmentation services include?
Webify.AI's AI staff augmentation services start with named engineers you interview and a two-week trial. Replacement is free within five working days, and the IP in all code is assigned to you. We sign your NDA before the first call. Engineers overlap with UK or US hours, and hourly plans are billed against timesheets.
| Task | Who handles it |
|---|---|
| Setting priorities and writing tickets | Your team |
| Daily direction and code review standards | Your team |
| Access to repositories, data and tools | Your team grants it, and you decide the scope |
| Choosing the engineer | You, after interviewing the profiles we put forward |
| Employment, pay and equipment | Webify.AI |
| Replacement if the engineer leaves | Webify.AI, free within five working days, with a handover overlap |
| Timesheets and invoices | Webify.AI, every two weeks on hourly plans and in advance on monthly plans |
| Review of AI-assisted code | A person reviews every AI-assisted change, and your normal code review still applies |
| Keeping your code out of public AI tools | Webify.AI, on every project |
The split matters. If you want a provider to own the outcome, staff augmentation is the wrong model, and project outsourcing fits better.
Every engagement also includes these contract terms:
- We sign your NDA before the first call.
- You own all the code: IP is assigned to you.
- Developers are named in the contract and never swapped without your agreement.
- No subcontracting without your consent.
- A person reviews all AI-assisted code, and your code never goes into public AI tools.
What does machine learning staff augmentation cover?
Machine learning staff augmentation adds engineers who build systems that learn from data. At Webify.AI, that work is mainly with language models: AI agents, retrieval over documents, LLM integration, and deployments on IBM watsonx and open-weight models. For other kinds of machine learning, tell us your stack and we will say honestly whether we have a match.
Machine learning is a wide field. Some teams need models trained on their own tables of data. Others need language models connected to documents and tools. These are different skills, and a provider should tell you which ones it has.
| Kind of work | Examples | Can Webify.AI staff it? |
|---|---|---|
| Systems built on language models | Agents, RAG, summaries, classification and extraction | Yes. This is the work of our AI / LLM and senior AI engineers. |
| Model deployment on your infrastructure | Open-weight models on your own servers, or IBM watsonx | Yes |
| Data pipelines in Python | Cleaning, moving and preparing data for AI features | Yes, through our Python developers and AI engineers |
| Classical machine learning | Forecasting, scoring and recommendations trained on your own data | Tell us your stack first, and we will say honestly whether we have a match |
| Computer vision and speech | Image classification, object detection and transcription | Ask us before you plan around it |
If your need is mainly classical machine learning, read more about that role on hire machine learning engineers.
Machine learning work also depends on tools. Training and deployment often run on cloud AI services, with MLOps tools to track experiments and models. Tell us what you use, and check the engineer's experience with it in the interview.
How do I set up a dedicated AI development team?
Decide the roles, then request profiles for each one. You interview and choose every engineer, and each is named in the contract and billed at their own rate. Appoint one technical lead, often a senior AI engineer, so the team has a single voice. Then agree working hours, rituals and where documentation lives.
A dedicated AI development team is staff augmentation at a larger scale. The engineers work only on your product, for months rather than weeks. A dedicated machine learning team works the same way, with the skills mix shifted towards data and models.
- 1
Name the outcome
Write down what the team should deliver in its first three months. That shapes which roles you need.
- 2
Choose the roles
A practical shape is one senior AI engineer, one or two AI / LLM engineers, and a senior developer for product integration.
- 3
Interview and choose
We put forward engineers whose experience matches your stack and seniority. You interview each one.
- 4
Appoint a lead
One person owns technical decisions. On your side, that may be your CTO; inside the team, the senior AI engineer.
- 5
Set the rituals
Hold stand-ups inside the overlap hours, a weekly demo and a regular review of the evaluation results.
- 6
Keep knowledge in your systems
Design notes, prompts, test sets and runbooks live in your repositories and wiki, not in anyone's head.
Swipe the table sideways to see every column.
| Role | 80 hours, billed hourly | 160 hours, billed hourly | 160 hours, monthly plan |
|---|---|---|---|
| Senior AI engineer | $4,800 | $9,600 | $8,150 |
| AI / LLM engineer | $3,600 | $7,200 | $6,100 |
| Senior developer | $2,800 | $5,600 | $4,750 |
| Mid-level developer | $2,000 | $4,000 | $3,400 |
Monthly plans are billed in advance and cost about 15% less than 160 hours at the hourly rate. Hourly plans are billed every two weeks against timesheets.
How does an augmented AI engineer start in your team?
On day one, the engineer gets access to your repositories, tickets, chat and any data they need, then joins an introduction call. In the first week they join stand-ups and open their first pull requests. By the end of the two-week trial, you know whether to continue, change plans or ask for a replacement.
AI engineers need a little more than access to code. They need examples of the problem, a way to measure progress and clear limits on data. Prepare these before day one:
- Sample data with personal data removed, or a written rule on which data they may use.
- Accounts for the model providers, cloud or platforms you already use, with spending limits set.
- A handful of real examples: questions users ask, and what a good answer looks like.
- The name of the person who approves anything that touches production.
- Your company's AI policy, if you have one. Our engineers follow it instead of our default rules.
In the first week, ask for a test set before any prompt tuning. It gives your team a number to track, and it makes the decision at the end of the trial easier.
When is AI staff augmentation the wrong choice?
Staff augmentation is the wrong choice when nobody on your side can set priorities or review the work. It is also wrong when you need a provider to own a fixed result, or when the work is under 80 hours a month. Then project outsourcing, a freelancer or waiting until the work is clearer will serve you better.
- Nobody can direct the work. Augmented engineers follow your priorities. Without someone to set them, an engineer can stay busy without moving the product forward.
- You want the provider to own the result. Augmentation sells time and skill. If you need a fixed outcome for a fixed price, outsource the project.
- The work is very small. Our hourly plans start at 80 hours a month, so a few days of work may suit a freelancer better.
- Your procurement requires certifications we do not hold. Our security page sets out what we do and do not have.
Saying this up front saves both sides a trial that was never going to work.
Frequently asked questions
Is AI staff augmentation the same as hiring a contractor?
Close, with two differences. The engineer comes through a company that replaces them if they leave. The contract also assigns the IP and rules out subcontracting. With an individual contractor, you handle replacement and contract terms yourself.
Who manages augmented AI engineers day to day?
You do, or the lead you appoint. The engineers take priorities from your team, join your stand-ups and work in your tools. Webify.AI handles their employment, equipment, timesheets and replacement.
Can I change the number of hours each month?
Yes. You can change the hours you buy from month to month. Hourly plans start at 80 hours a month, and monthly plans cover 160 hours billed in advance.
Can one augmented engineer grow into a dedicated team?
Yes. Add engineers as the work grows. Each one is put forward for your interview, named in the contract and billed at their own rate.
How much does a dedicated machine learning team cost?
It depends on the mix. One senior AI engineer and two AI / LLM engineers on monthly plans cost $20,350 a month in total. A senior developer for product work adds $4,750 a month.
How is AI staff augmentation priced in the UK?
In pounds sterling. AI / LLM engineers cost £36 an hour, or £288 for an 8-hour day. Senior AI engineers cost £48 an hour, or £384 a day. Mid-level and senior developers cost £20 and £28 an hour.
Do augmented engineers work in our time zone?
For part of the day. UK teams: 09:00 to 13:00 UK time every working day, inside a normal Indian working day, at no extra cost. US teams: 09:00 to 12:00 US Eastern time through an evening shift, at 15% extra. The rest of the day is focused, asynchronous work.
What happens to our data during augmentation?
You decide which systems and data the engineer can reach. Your code and data never go into public AI tools. If the engineer will handle personal data, we agree data-protection terms with you before they start.
Can augmented AI engineers work alongside our in-house AI team?
Yes. They follow your team's conventions, review process and architecture decisions. Pairing them with an in-house engineer in the first weeks helps them learn your system faster.
Will your engineers follow our AI policy?
Yes. If your company has its own AI policy, our engineers follow it instead of our default rules. Share it before the engineer starts, along with any rules on data access.
Do you offer staff augmentation for roles other than AI?
Yes. Mid-level developers at $25 an hour and senior developers at $35 cover React, Next.js, Node.js, Python, mobile and Shopify work. See hire developers.
Request AI engineer profiles for your team
Tell us the role and when you need someone. We'll email two named engineers with their experience and availability within 48 hours, and you choose who to interview.
- No cost to receive profiles
- Two-week trial with the developer you choose. No charge if you stop within the first five working days.
- Invoiced in USD or GBP; IP assigned to you.