Principal AI Engineer, Artificial Intelligence Collaboration Centre (AICC) – 2 posts

Ulster University
Coleraine
4 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist

Artificial Intelligence Engineer

Software Engineer, Applied Artificial Intelligence (AI)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Principal Machine Learning Engineer




Principal AI Engineer, Artificial Intelligence Collaboration Centre (AICC) – 2 posts




 


Role:  Principal AI Engineer, Artificial Intelligence Collaboration Centre (AICC) – 2 posts


Department: School of Computing, Engineering and Intelligent Systems


Grade: Business Support Grade 9 (£60,001 per annum)


Responsible to:   Deputy Director of AI and Technology Research Services


Campus:  Derry~Londonderry OR Belfast


 


(Fixed-Term until 31st August 2028 / Full-Time)


 


Job Purpose:


 


The Artificial Intelligence Collaboration Centre (AICC) is a £16.3M investment by InvestNI and the Department for the Economy to create a partnership between Ulster University and Queen's University based predominantly in Belfast and Derry/Londonderry.


 


The AICC has the aim of increasing the use of AI by local companies in Northern Ireland by collaborating on a series of applied technology projects. It offers an exciting opportunity for the successful candidates to help lead a world class team delivering real-world value from AI and engaging with a wide range of academics involved in applying AI in their research and with industry.


 


As a Principal AI Engineer in the AICC team, you will work with the AICC Research Lead to develop the skills and experience of the full team of AI/ML engineers. You provide day to day leadership for the team, specifically around framing and delivering collaborative research and development efforts with companies across wide areas of AI, ML & Data Science.


 


The School of Computing, Engineering & Intelligent Systems holds a Bronze Athena SWAN Award in recognition of our commitment to advancing Gender equality in higher education.

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.