Principal Application Software Engineer - grads welcome

Adecco

Cambridge

1 year ago

Applications closed

Related Jobs

View all jobs

Senior Simulation Engineer (Data Science)

Principal Data Scientist

Faculty Fellowship Programme - Data Science - May 2026

Lead Software Engineer (Machine Learning)

Senior MLOPs Engineer

Senior Machine Learning Scientist

This job description is for a Principal Application Software Engineer role based in Cambridge, UK with a hybrid working model and graduates are welcome to apply: Here's a breakdown of the key points:About the CompanyA pioneering machine learning and artificial intelligence software house.Renowned for developing cutting-edge technologies and highly respected in the AI domain.Led by experienced entrepreneurs with a history of producing award-winning tech companies.The team includes some of the brightest minds in technology.Job ResponsibilitiesTechnical Leadership: Manage and oversee complex technical projects within a commercial setting.Communication: Adapt communication style to work effectively with a diverse software team.Team Mentoring: Lead and mentor a small team, fostering growth for junior team members.SDLC Expertise: Proficient in the full software development life cycle-design to implementation.Required Skills and QualificationsEducation:Degree educated with a 2.1 or higher in a relevant field (Computer Science, Physics, Natural Sciences, Engineering, etc.).Mathematically inclined with strong problem-solving abilities.Technical Expertise:Hands-on experience with the following:Node.js, Python, JavaPostgreSQL, Elasticsearch, RedisGeneral engineering mindset and problem-solving skills.Professional Experience:Several years of experience in a commercial setting managing complex technical projects.Proven ability to lead a ...

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.