Artificial Intelligence Engineer

Be-IT
Glasgow
2 months ago
Applications closed

Related Jobs

View all jobs

Computer Vision and Artificial Intelligence Engineer

Research Software Engineer: Geospatial Artificial Intelligence (Geo-AI)

Software Engineer, Applied Artificial Intelligence (AI)

Software Engineer, Applied Artificial Intelligence (AI)

Geospatial Artificial Intelligence Research Scientist

Artificial Intelligence Manager (18-month FTC)

Are you a passionate engineer who is looking to test their knowledge and skills within AI in a professional environment? Are you looking to deliver real world AI solutions across a range of product portfolios with global clients?


You have the opportunity to join a business at the forefront of their industry as they match their market expansion with innovation, research and development to ensure they are continually evolving


In this hands on technical role you will design, build and deploy AI and automation features that will have large scale tangible results for a number of key users both internally and externally.


This role will come with the autonomy to research new ways of working, create proof of concepts to support your thoughts and have the support of the business Head of Data and Development Manager to help you in put your own ideas.


You will work in an extremely collaborative and cross functional organisation meaning you will have the support and the visibility of all aspects of the business to help you make informed decisions to drive company wide innovation and operational improvement


In order to be successful in this role the ideal candidate will come from an engineering background, experience building and managing AI agents and a solid understanding of LLM behaviour/prompt engineering


Curious? Contact me for more details on , or message me directly on LinkedIn.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.