How to Hire AI Developer for a Business Project: 9 Essential Steps

The adoption of artificial intelligence has been making automation of processes, better decision-making processes, user personalization, and development of digital products easy for business organizations. Transforming an idea about AI into an efficient business solution needs not only to choose the proper technology, but also the correct expert to implement the solution.

Information on how to hire an AI developer will help you to avoid making mistakes when it comes to hiring and minimize the technical risks, ensuring that your investments will bring some value to the business. Companies that need to hire AI developers must start by realizing their requirements and needs first.

A startup that develops products based on artificial intelligence, a business owner that wants to automate some processes with the help of artificial intelligence, and a tech professional who needs to incorporate AI solutions into the existing system – no matter what position you hold, first of all, you have to understand your requirements. You can choose an AI developer and evaluate his or her technical skills and different possibilities of hiring.

Here we will discuss nine important aspects to take into account when hiring an AI developer.

1. Define Your AI Project Goals and Requirements

Define what it is you expect from your AI before you look for developers. Without a clearly defined goal and scope of work, hiring an AI developer will not only be a waste of time but will complicate things for you even further. Before you hire AI developer talent, establish what success will look like for your business.

You have to know what kind of issue within your business you want to address. Don’t just make a decision to implement AI into your business operations – think about what kind of automation, what kind of predictions or what kind of generated content can make a change for you.

Identify measurable business objectives

Now that you understand the problem statement, it’s time to establish objectives and KPIs for your project. These will assist your AI vendor to make proper technological choices and ensure an objective way of assessing its performance.

The metrics relevant to your application might be as follows:

• Operational efficiency – decrease the time it takes for employees to perform monotonous tasks.

• Customer experience – increase response times or customer satisfaction.

• Accuracy – decrease the number of mistakes in document extraction, classification, and predictions.

• Cost-efficiency – reduce the costs of performing one certain business process.

• Revenue – increase conversion rates, personalization, lead qualification.

Identify the current baseline wherever possible to compare the performance before and after implementation of the AI solution.

Document the project scope

Create a project brief where you specify who your users are, needed functionalities, existing systems, data sources, budget, and timeframes for delivery.

In addition to that, identify if there are any privacy, security, integration or regulatory requirements that might affect the development process.

It’s not necessary for you to be aware of all the technical requirements before involving the developer. It’s important for you to understand what kind of outcome you want to achieve, and what are the constraints of the developer.

Practical suggestion: Start with creating an MVP to resolve a particular business issue.

2. Find Out What Kind of AI Developer You Need

There are many aspects associated with the development of AI solutions, and each one of them requires a particular set of skills. Realizing their difference will help you to choose the necessary specialists without searching for those who possess knowledge of all AI solutions. When you hire AI developer specialists, match their expertise to the specific technology your project requires.

Machine learning engineers

For engineers using machine learning technology, they are preoccupied with developing machine learning models. Some of the things that they do include forecasting demands, detecting frauds, maintaining predictive mechanisms, making recommendations, and predicting customer attrition.

Generative AI and LLM developers

Applications by generative AI developers make use of LLMs along with other generative technologies. The job functions of these developers might involve prompt creation, retrieval of augmented generation, tool call, structured output, and integration of AI models within business applications.

These applications might be suitable for internal knowledge assistants, document QA systems, content workflows, and conversation interface.

AI application developers

Application developers of AI functionalities build web pages, mobile applications, enterprise applications, and other business systems using AI functionalities. Normally, they combine AI APIs with back-end development, database integration, security measures, and UI development.

Would it be better to engage one developer or a team?

In case if the prototype is limited or less complex in terms of AI, one developer is enough. In case of more complex projects, the knowledge of AI engineers, data engineers, back-end developers, security experts, and product managers could be needed. 

3. Establish Your AI Development Budget and Timeline

Through budgeting, you can be able to get proper candidates and also make fair comparisons between your proposals so that you do not underestimate the costs involved in developing the solution.

There is no fixed cost to hire AI developers as there are many factors such as experience, location, specialization, complexity of projects, engagement type, and infrastructure among others that affect this process. If you plan to hire AI developer services, account for these factors before comparing proposals.

Understand the factors affecting development costs

Consider the following aspects when planning your budget:

• The experience level of the developers: Although it is going to cost you more to hire experienced developers, they can help resolve any technical difficulties that arise.

• Complexity of the project: The development of the custom solution, the particular analysis, and complex integrations will take more time than the application of the existing one via API.

• Quality of the data: Poor quality data will result in additional effort.

• Infrastructure: The need for cloud computing, storage, monitoring, and use of the models can involve ongoing costs.

• Testing and security: The production system needs to be tested, protected, and managed.

• Maintenance: Your AI app might need maintenance and subsequent evaluation.

Choose the right pricing structure

There are three main structures that businesses usually apply.

• The hourly or daily pricing: Appropriate when the requirements change or there is some work related to experiments.

• The fixed price agreement: Useful in case the requirements and deliverables are clearly determined. The big changes in scope may affect the contract.

• The monthly retainer or dedicated teams: Relevant for long-term development, improving products, and technical support.

All the above models have pros and cons. Choose depending on the uncertainty, duration of the project and management skills.

Account for the total cost of ownership

It is important to consider more than just developer fees. Model API use, hosting services, third-party software, database hosting, implementation and deployment, monitoring and maintenance, should all be considered in the financial analysis.

Projects that are likely to have many technical unknowns might benefit from a proof-of-concept stage prior to the main project implementation.

4. Choose the Right Hiring Model

Now having taken into account all your requirements and your budget, you can decide on how to proceed with your choice either with regards to hiring an AI developer who will be working for you as a freelancer or joining hands with an AI development company. The right model can make it easier to hire AI developer expertise that fits your business.

There are various factors which have to be considered while making such a decision.

Hiring a freelance AI developer

A freelance developer can work out in a situation where there is a limited scope of the project, where it is short-term, prototyping, and integration of some specific kind. Businesses that hire AI developer freelancers can benefit from flexible arrangements for specific tasks.

Availability and expertise might be restricting factors with freelancers. Nevertheless, their advantage is mostly seen when there is someone inside your company to oversee the project.

Hire an in-house AI developer

The internal developer is able to gain long-term expertise in your company, interact with your staff on a regular basis, and make contributions to product development on an ongoing basis.

This option can be considered in the event that artificial intelligence is the core part of your product and your operations, and requires significant resources. Deciding to bring in-house AI developer talent can help drive ongoing product development.

However, recruitment, pay, training, turnover and career development continue to be challenges for you. In fact, one may require other experts for different phases of the AI life cycle.

Work with an AI development company to build your AI solution.

An AI development company may have a variety of technical skills, project management experience and delivery processes. AI developer teams provided through an external partner can offer a broader skill set to companies.

This can be useful if you don't have an AI team and need a whole solution.

Before you make a choice on your partner, check out case studies of the company, make sure to identify who they will be working with, and find out how they'll test, document, manage IP, and provide support after the product is launched.

Compare your options

5. Find Qualified AI Developer Candidates

Once you define the requirements and the hiring model, you'll start searching for candidates with experience in the area that is relevant to your project. For successful hiring of AI developer candidates, it's important to look for the right experience and not the number of technologies that they include in their CVs.

You want a broad reach because that's when you have the opportunity to find some talent, but you want to make it a show to compile a list of professionals who can do it.

Finding potential candidates in various hiring avenues

Below are some of the possible ways you may use to identify the right people to work for your project.

Professional networks, developers’ communities, open source projects, recruitment websites targeting technical hiring, freelancing platforms, and AI developers’ companies.

Suggestions made by reputable technical experts would also be helpful in identifying individuals with the required skills and experience.

Job description

The job description must give a clear view of the business challenge and the tasks that need to be performed by the developer.

It should include:

• Objectives and target users of the project.

• Technical skills required and experience of the developer.

• Deliverables expected and responsibilities.

• Preferably experience with similar projects.

• Type of engagement, timeframe and collaboration requirements.

• Range of budget or compensation structure, where applicable.

Essential and desirable skills should be separated. Requiring experience with all existing AI frameworks can unjustly rule out the applicants who have skills more suitable to your project.

Evaluate portfolios and commercial projects

Search the previous projects to find out some examples of implementation, problem solving, testing and deployment.

Inquire into the contributions of the candidate to the project, decision making and achievements. Sometimes just one portfolio project demonstrating a tested finished product is more useful than a whole list of implemented technologies.

For the commercial projects make sure to differentiate between the work of the candidate and the accomplishments of the whole company/team.

6. Test Technical Skills via Practical Evaluation

Résumé can show experience, but cannot prove the ability of the candidate to solve your business problems. Practical evaluation will help you understand technical judgment, implementation skills and knowledge of limitations. Before you hire AI developer candidates, use practical assessments to verify their abilities.

Verify relevant technical competencies

The requirements vary according to the specific role but can include:

• Programming languages like Python and related application languages.

• Data processing, database management, and API implementation.

• Basic knowledge of machine learning, as well as model evaluation.

• Testing, version control, deployment, and monitoring of software.

• Security principles and good practices of data management.

Thus, while a developer adding an existing LLM to a business application does not need to create any foundation models, they have to know the limitations of the given models and evaluate its outputs.

Use realistic technical assessment

Once you've created a list of suitable candidates, provide them with a small, time-boxed task which reflects the actual tasks they will have to do in their new job.

If we assume that your firm requires an AI assistant who will provide answers to some questions related to the internal policies of the company, then one can ask the candidates to come up with a solution based on specific documentation, explain how specific parts will be located and how the candidate will prove that the answer is justified by the sources.

Ask targeted interview questions

Examples of AI developer interview questions are:

• How to know which is better: reusing the AI model or creating the custom model?

• What steps do you take to verify an AI solution before it's used?

• What should be done to minimize the number of answers that are not supported in the document oriented AI assistant?

• What would you do to ensure that the company's sensitive information does not fall into the hands of an outsider that could use the AI service?

• What will you need to keep an eye on after you have the AI solution deployed?

It is important that the top people can tell you why you did what you did, understand that there are compromises, and that they are willing to settle for 'maybe' rather than 'must' and 'must'.

7. Evaluate Communication, Security, and Collaboration

Knowledge alone cannot do the trick. Effective communication, proper judgment and high-level security are all characteristics of an AI system. An individual who possesses technical skills but poor communication skills and is unaware of the risks associated is a risk of delaying any project. When you hire AI developer experts, look at these characteristics together with their technical skills.

Assessment of Communication and Problem-solving skills

During the interview of the candidate, you can judge his/her ability to form questions, his/her explanation of some technical terms and assumptions he/she made of any potential problem that may occur in the delivery of the work.

They may be asked to give an example of a project where they failed due to their approach to it. This way, you will get an idea of how they analyze problems and handle failures.

Discuss data security and AI practices that respect privacy

Before revealing any secret information and allowing access to the system, ask yourself if the candidate can keep you safe from any harm.

Important elements are:

• Appropriate access restrictions and least privilege principle.

• Confidentiality agreement and appropriate handling of credentials.

• Data retention and data processing by third party AI vendors.

• Securing any personal, financial and proprietary data.

• Testing for erroneous, biased or harmful results if needed.

• High level involvement in decision making by an individual.

The security measures are to be chosen based on the use case, data and compliance needs.

Verify collaboration and documentation process

How would the candidate report on the progress, document technical decisions, conduct code reviews and address issues?

Discuss the manner of communication, frequency, timing and issue resolution, should a problem arise before starting the cooperation.

Tip: Think of communication and documentation as an important part of evaluation of the developer.

8. Finalize the Contract, Deliverables, and Ownership

Scope and Deliverables

If you are entering into an agreement, it is very important that it is clearly specified as to what is expected from both parties.

This may include source code, application functionalities, model configurations, integration, testing, documentation, delivery and handover documentation.

Set up milestones and review dates and also how additional costs for changing the initial scope are determined.

With respect to AI projects, set up the acceptance criteria considering the type of the project. Set the criteria for evaluation and not just assume that an experimental model is guaranteed to give the same result always. Before you hire AI developer services, make sure these criteria are agreed upon.

Clarify intellectual property and data rights

Indicate which entity has the right to own any custom code and other deliverables that are associated with the particular project.

Clarify how the existing code, third party libraries, models licenses, dataset, prompt, evaluation resources, etc., can be utilized given that each of them might have its own terms of use.

Confidentiality clauses must also be considered and access to and use of project data must be discussed as well. Due to confidentiality or intellectual property concerns, there may be a need to consult with a lawyer.

Set up payment and accountability systems

Make connections to milestones whenever possible. Who approves deliverables? Who will give the information and access? Who is responsible for deployment and maintenance?

Briefly describe how to react to issues that are caused by delays, inaccuracies, extra needs and disagreements.

Note: Be sure to agree on the work scope, acceptance criteria, costs, intellectual property, security issues etc. before signing, etc.

9. Start with an MVP and Measure Results

Getting an AI developer on board is just one step. There should also be a process for delivering the solution and validating its performance. Businesses that hire AI developer professionals should plan for ongoing evaluation after the initial implementation.

One good option in case there is much uncertainty about the project and potential waste in resources may be to start with the minimum viable product.

Starting with a minimum viable product

Instead of creating the solution in full extent right away, it would be worth figuring out what its minimum useful variant can be.

As an example, a company that is going to develop an internal knowledge assistant might consider starting with a minimal amount of documents approved for processing and minimal number of employees.

In cases of generative AI deployments, make sure to employ representative evaluation instances and human oversight when appropriate. Track the quality of the output, latency, and costs associated with deployment as performance can be affected by changes in the data and models used.

Make plans for maintenance and scalability

Determine how the system will be maintained, incidents handled, dependencies managed, costs tracked, and evaluated going forward.

A production-ready AI application requires proper operation management, not just the successful initial deployment.

Useful action step: Test your developer’s work based on the reliability and applicability of the solution you received.

What Should You Look for When Hiring an AI Developer?

When considering your choices, go for:

• Experience with relevant business problems.

• Good technical skills with regard to the particular AI technology you intend to use.

• Sound problem solving and architectural skills.

• Good testing, evaluation, and implementation skills.

• Proper security and handling of information.

• Effective communication and collaboration.

• Good results from past projects.

It is not necessary that each time you need the most experienced and skilled person in AI. The best option is definitely going to be the one whose skill sets complement yours. If you employ artificial intelligence development skills that complement your team’s capabilities, you will be able to develop an application that fits your business.

Frequently Asked Questions About Hiring an AI Developer

How much is the cost of engaging with an AI developer?

It largely depends on the level of experience and specialization of the developer, the region where the work will be done, the type of engagement you opt for, and other factors. A simple AI implementation can consume fewer resources than the development of a machine learning algorithm along with its preparation and deployment.

Should I choose a freelance AI developer or an AI development company?

Depending on the specific situation, the freelance option could be right for the narrow assignment or project in case you have technical experts within your company. When you need a range of specialists involved and even project management, consider the option of an AI development company. Compare the suggested team, the cost, the accountability, and support afterwards.

How can I evaluate an AI developer's experience and skills?

Study the projects done by the developer, find out about his individual contribution to the project, make an actual test, ask about testing, the architecture, the security, deployment.

Conclusion: Hire AI Developer Who Understands Your Business

Finding the proper AI software engineer will entail the need to have an approach whereby technical proficiency is matched with business needs. Define the problem you are facing, choose an expert, set your budget and pick a good recruiting option. Then screen the developers based on their experience, assessment and talk about security and collaboration.

Before the work starts, come to an agreement regarding deliverables, ownership and criteria of acceptance. While working with an AI developer, rely on a well-targeted MVP and key performance indicators.

But the main aim of this process is not in finding an engineer who will create AI software for you. Your final purpose should be in finding an expert who will convert your requirements into a reliable, supportable solution which would bring real value to your business.

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