Senior Frontend Engineer

CATCHES
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior MLOps Engineer

Artificial Intelligence Consultant

Principal Data Scientist & Machine Learning Researcher

Principal Data Scientist & Machine Learning Researcher

Principal Data Scientist & Machine Learning Researcher

Senior Machine Learning Research Engineer

CATCHES are a pre-seed start-up backed by some of the most influential names in luxury fashion globally. We've partnered with the global leaders in cloud computing and AI to integrate advanced 3D rendering, Artificial Intelligence (AI) and Visual Effects (VFX) techniques to create unparalleled shopping experiences for luxury fashion and exclusive events.


The role


Apply your expertise in modern frontend technologies to design, develop, and implement intuitive interfaces that delight our users. From conceptualization to deployment, you will have the opportunity to contribute to every stage of the development lifecycle, ensuring our products are both visually stunning and highly functional.


Tech stack


  • NextJS, Typescript, (S)CSS, HTML
  • Google Cloud Run, Firebase, Vercel
  • Google Workspace, JIRA, Excalidraw
  • Datadog


Working at CATCHES


  • Remote working with some in person collaboration (London)
  • Equity opportunity in pre-seed cutting edge tech firm with household name backers.
  • Highly collaborative and motivated team with depth and breadth of experience across Video Games, Films and Tech.


Responsibilities


  • Develop, and maintain multiple front end web applications
  • Collaborate with back end developers, data engineers, and other stakeholders to ensure seamless integration of front end and back end components.
  • Write clean, maintainable, self-documented code.
  • Implement best practices for security, scalability, and performance.
  • Participate in code reviews and provide constructive feedback to peers.
  • Stay updated on industry trends and best practices in backend development.


Requirements


  • Solid experience in frontend web applications in a JS based framework
  • Proficiency in consuming Web APIs to produce front end outputs
  • Experience delivering pragmatic solutions and implementing iterative design approaches
  • Familiarity with version control systems such as Git.
  • Strong communication and collaboration skills.
  • Ability to work effectively in a fast-paced and dynamic environment.

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.