Back End Software Developer

i4 Jobs

Doncaster

1 year ago

Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Experienced Recruitment Consultant – Artificial Intelligence & Bio Artificial Intelligence Manchester (Hybrid)

Recruitment Team Manager – Artificial Intelligence (UK Market Focus) Manchester (Hybrid)

Experienced Recruitment Consultant – Artificial Intelligence

Recruitment Team Manager – Artificial Intelligence (US Market Focus) Manchester (Hybrid)

Software Engineer, Applied Artificial Intelligence (AI)

Description

Back End Software Developer – Fully Remote Working – Salary – £50 – £65k (Negotiable) – Permanent

A very exciting opportunity for experienced Back End / Azure Focussed Software Developers to work with one of the UK’s Top 50 scalable Tech Business’s operating in the Fintech Space. They are an established product owner with a global portfolio of clients. The business is in a very exciting period of growth and have a new opportunity for experienced Software Developers to join their development team. You will be working on Greenfield projects with focus towards Machine Learning and Azure.

We are looking for developers to have experience of the following:

.Net Core 3.1 and above with C# Building secure REST APIs using MVC Web Api TDD/Unit testing Use of entity mocking frameworks such as Automoq EF Core

Desirable

Azure Service Fabric Machine Learning using Azure ML Studio/Azure Machine Learning Containerisation and Kubernetes in an Azure domain

Benefits

Competitive Negotiable Salary Fully Remote working – UK Based Flexible Working Hours 25 Days Holiday / year + Bank Holidays Employee Incentive Package Company Pension Genuine Career and technical capabilities progression

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

Industry Insights

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

Feb 9, 2026

Careers

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.

Feb 2, 2026

Jobs

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.

Jan 23, 2026

Education

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.