Hiring an AI Engineer is not the same as hiring a general software profile or a data specialist. Companies need professionals who can understand artificial intelligence models, work with machine learning systems and help bring AI initiatives closer to real business use cases.
At NBS, we help companies recruit AI Engineers with the right technical experience, but also with the judgement needed to work in complex and fast-moving environments. We focus on understanding the role, the maturity of the AI project, the technical stack and the kind of person your team really needs before starting the search.
Need to hire an AI Engineer?
Tell us what kind of AI profile your company needs and we will help you define a realistic search.
AI Engineer Recruitment is a specialised hiring service focused on finding professionals who can design, develop, test and support artificial intelligence solutions. Depending on the company and the project, this can include AI Engineers, Machine Learning Engineers, Applied AI Engineers, Generative AI Engineers, NLP Engineers, Computer Vision Engineers or AI Developers.
We review the technical requirements of the role, the level of seniority, the type of AI project, the production environment and the expectations around the position. Some companies need experience with machine learning models, Python, deep learning frameworks, NLP, LLMs, prompt engineering, computer vision or model evaluation. Others need someone who can connect AI systems with software products, APIs, cloud environments or internal business tools.
The goal is not only to find someone who has studied artificial intelligence or worked with a specific model. A good AI Engineer needs to understand how AI can be applied, tested, monitored and improved in a real environment. That difference is important, especially when companies want to move from experimentation to useful AI solutions.
Looking for AI engineering talent with real project experience?
We can help you clarify the role, understand the market and identify candidates who fit your technical needs.
AI Engineer hiring is becoming more complex because the term can mean very different things depending on the company. In some teams, an AI Engineer works close to machine learning models, data science and research. In others, the role is more focused on applying AI to digital products, automation, chatbots, recommendation systems, natural language processing, computer vision or generative AI features. That is why the first step is not searching blindly, but defining what kind of AI Engineer your company actually needs.
We pay attention to the difference between research-oriented profiles, machine learning engineers, applied AI engineers and software engineers with strong AI experience. These profiles can overlap, but they are not always interchangeable. A company building an internal AI assistant, a SaaS product with generative AI features, an automation platform, a computer vision solution or a machine learning-based recommendation engine may need different skills, different seniority and a different hiring message.
NBS works with honesty, realism and a boutique recruitment approach. We are not here to send a large number of profiles and hope that one of them works. We want to understand your company, the salary range, the technical environment, the working conditions and the expectations around the position. From there, we search, approach and evaluate candidates with a clear view of what can realistically be found in the market.
Our experience in IT recruitment helps us look beyond keywords such as AI, machine learning, Python, LLMs or generative AI. We review whether candidates have worked on real projects, how they understand model performance, product integration, scalability, data quality, testing and collaboration with engineering teams. The result is a more focused process, a curated shortlist and a better chance of finding someone who can contribute to your AI goals without creating unrealistic expectations.
Need a realistic view of the AI Engineer market?
We can help you assess the role, the salary range and the type of candidates available before starting the process.
We can help companies recruit AI Engineers, Machine Learning Engineers, Applied AI Engineers, Generative AI Engineers, NLP Engineers, Computer Vision Engineers and AI Developers. The exact profile depends on the project, the technical environment and the level of ownership needed.
An AI Engineer usually needs experience with Python, machine learning, model development, data handling, APIs and software engineering practices. Depending on the role, experience with deep learning, NLP, LLMs, generative AI, computer vision, cloud platforms or model deployment may also be relevant.
We review their previous AI projects, technical stack, level of autonomy, model experience, programming skills and ability to work with product, data or engineering teams. We also look at motivation, communication, salary expectations and fit with the company.
The two roles can overlap. A Machine Learning Engineer is usually focused on building, training, improving and deploying machine learning models. An AI Engineer can have a broader role, often applying AI systems to products, automation, internal tools or business processes. The exact difference depends on how each company defines the position.
Yes. Generative AI Engineer recruitment usually requires a precise definition of the role, because some companies need LLM integration, others need prompt engineering, product development, model evaluation, AI agents, automation or experience connecting generative AI features with existing platforms.
AI Engineering is a fast-moving field and many candidates use similar keywords on their CVs. The difficulty is understanding who has real project experience, who has only experimented with tools and who can work in a production environment. A clear role definition and a realistic view of the market are essential.
