Senior Full-Stack Engineer

Scopeworker
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - AI Practice Team

Senior Data Scientist - AI Practice Team

Senior Machine Learning Research Engineer

Senior Machine Learning Engineer

Senior Data Scientist

Senior Machine Learning Engineer

Qualifications

Bachelor's or Master's degree in Computer Science or similar (PhDs will be given preference)7+ years of experience in full-stack development; from UI to backend systemsFull proficiency in Angular.JS and / or Angular 2+ (Angular 17)Full proficiency in Node.JS and JavaScript ES6+Experience with NestJS is preferred but not necessaryProficiency in relational databases is necessaryExperience with management tools like Jira and ConfluenceA good working proficiency in verbal and written EnglishAbout this Job Scopeworker's software engineers are developing a next generation, enterprise platform. We are looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile. As a software engineer, you will work on a specific project critical to the Scopeworker platform with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance Scopeworker's software.

Do you have the skills to fill this role Read the complete details below, and make your application today.About Scopeworker Scopeworker is an enterprise SaaS. It digitalizes the Procure-Execute-Pay lifecycle of supplier services for critical infrastructure. The automation enables significant cost, time and quality efficiencies for both buyers and suppliers and enables a live situational awareness of procurement, finance, operations and other stakeholders departments. Scopeworker can be used standalone or as a digital layer over the top of Oracle, SAP or Microsoft Dynamics ERPs. Scopeworker processes billions of dollars of services each year for the Fortune 100.

#J-18808-Ljbffr

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.