Customer Success Engineer

Holborn and Covent Garden
11 months ago
Applications closed

Related Jobs

View all jobs

Forward-Deployed Data Scientist

Senior Forward-Deployed Data Scientist

Senior Simulation Engineer (Data Science)

Senior Machine Learning Engineer, Search & Recommendations

Senior Machine Learning Engineer

Principal Machine Learning Scientist - Applied Research (UK Remote)

Our client, is leading the way in rebuilding the infrastructure that underpins the Travel Industry. Now recruiting a customer-centric individual to join their team as a Customer Success Engineer. This position offers a competitive salary range and is based in London with a hybrid working arrangement.

As a Customer Success Engineer, you will play a crucial role in ensuring client's receive exceptional support and guidance throughout their journey. You will be responsible for providing technical expertise, troubleshooting complex issues, and delivering solutions that drive customer satisfaction and success. Suggesting ways to use APIs to build the best travel experience for their users!

  • Act as a primary point of contact for customers, building strong relationships and providing exceptional support

  • Manage the implementation process with customers as they build a travel experience on top of their API tools

  • Answer product questions and resolve API issues via email, slack, and zoom.

  • Proactively identify and resolve technical challenges, ensuring timely and effective solutions

  • Conduct regular check-ins with customers to assess their needs, provide guidance, and gather feedback for continuous improvement

  • Monitor and analyse customer health metrics to identify trends, anticipate risks, and implement proactive measures to mitigate potential issues

  • Analyse customers needs and advise how they can use APIs to better meet them.

  • Continuously update your technical knowledge to stay current with our client's products, industry trends, and best practices

    Customer Success Engineer Skills and Experience:

  • Bachelor’s degree in Data Science, Business Analytics, Statistics, Computer Science, or a related technical field.

  • 5+ years in tech support helping enterprise customers use a RESTful API product

  • Experience integrating APIs, debugging integration issues, writing scripts and SQL queries.

  • Ability to read (and ideally write) code in multiple programming languages

  • Track record of expeditiously answering and solving product related questions

  • Eager to embrace the culture and objectives of a fast-moving start-up

  • Excellent communication skills with ability to express complex business and technology issues in a clear way.

  • Track record of engaging effectively with customer staff of all career levels

  • A plus: Knowledge of travel technology - specifically airline and/or hotel distribution systems

    Salary and Benefits:

    Our client offers a dynamic and collaborative work environment, with opportunities for professional growth and development. In addition to a competitive salary, you will benefit from a comprehensive benefits package, including:

  • Private healthcare insurance

  • Pension scheme

  • Enhanced Parental leave

  • Flexible working arrangements

  • 3 Company Parties each year

  • 27 days of annual leave, plus bank holidays

    If you are passionate about delivering exceptional customer experiences and thrive in a fast-paced, technology-driven environment, we encourage you to apply for this exciting opportunity with your updated cv

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.