BackEnd Developer - Abu Dhabi - 12 months - Relocation package

Abu Dhabi
11 months ago
Applications closed

Related Jobs

View all jobs

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

Experienced Recruitment Consultant – Artificial Intelligence

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

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

Machine Learning Engineer

Machine Learning Engineer

Backend Developer Role working for a consultancy based in Abu Dhabi

Role - BackEnd Developer

Duration - 12 months

Location - Abu Dhabi

Rate - £500 - £550 per day

Relocation - £10,000 relocation package (£5,000 expenses and £5,000 accommodation) and visa

Position Summary:

We are seeking a talented and motivated Senior Back-end Engineer to join our growing team. As a Senior Back-end Engineer, you will be working across the entire web stack, so a real passion to drive the product and technology forward is something that we highly value. You will work cross-functionally to deliver user-centric solutions to our customers and become an expert in developing high-quality technical solutions through continuous learning and collaboration.

Day-to-day responsibilities would include a combination of the following:

Design, develop, and maintain robust server-side applications and APIs to support front-end functionality and ensure seamless data flow.
Create and optimize database schemas, write efficient queries, and ensure data integrity, scalability, and security across various databases (e.g., SQL, NoSQL).
Ensure the security of applications by implementing robust authentication, authorization, and data encryption protocols.
Work closely with front-end developers to integrate user-facing elements with server-side logic and collaborate with DevOps to deploy and monitor applications effectively.
Analyse, troubleshoot, and optimize backend processes to improve application performance, reduce latency, and enhance the overall user experience.
Connect the application with third-party services and APIs, ensuring smooth data exchange and maintaining service reliability.
Adhere to coding best practices, including writing clean, maintainable, and well-documented code that can be easily understood and scaled.
Perform unit testing, integration testing, and debugging to ensure high-quality code and reduce the occurrence of bugs or errors in production.
Continuously monitor application performance, identify bottlenecks, and implement solutions to improve efficiency and reliability.

Apply for this role if you are:

Have experience in developing and deploying machine learning models with a proven track
Understand statistical analysis and hypothesis testing
Use data visualization tools (e.g., Tableau, Power BI) to present insights
Handle database systems and data manipulation
Excel in problem-solving and critical
Communicate complex technical concepts clearly to non-technical
Collaborate effectively in cross-functional teams and manage multiple projects

Qualifications:

Bachelor's or Masters Degree in Computer Science, Information Technology, or a related
Experience as a Full Stack Developer or in a similar role is a
Proficiency in server-side languages such as Java and
Familiarity with database technologies like Snowflake, Postgress, MySQL, Oracle,
Experience with version control systems like Git and continuous integration/continuous delivery
Strong problem-solving skills and troubleshooting
Familiarity with Agile development

GCS is acting as an Employment Business in relation to this vacancy

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.