Software Engineer

Great Chesterford
8 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer, Applied Artificial Intelligence (AI)

Software Engineer, Applied Artificial Intelligence (AI)

Lead Software Engineer - MLOps Platform

Lead Software Engineer (Machine Learning)

Data Scientist – Content Engineering

Digital and Technology Solutions Apprenticeship - Artificial Intelligence Software Engineering

Radar Software Engineer

Location: Cambridge

Type: Permanent - Hybrid working (3 days office/ 2 days remote)

Salary: Up to £50,000 depending on experience

About the Company

Tech Connect Group is working with an established Aero/ Defence Technology SME based in the wider Cambridge area. They are a leading designer and manufacturer of radar systems whose patented and industry-leading radar technologies are deployed in over 35 countries for applications including border surveillance, perimeter security, and infrastructure monitoring.

The Opportunity

Key Responsibilities:

Design and develop software for the company's radar systems.
Create software interfaces for integration with third-party surveillance and security systems.
Enhance and improve software functionality with a focus on user experience.

Required Qualifications & Skills

Proficient in C++ (Essential)
Strong understanding and hands-on experience with object-oriented software design.
Analytical and creative problem-solving abilities.
Comfortable working directly with end customers and users.

Preferred Qualifications & Experience

Degree in software engineering, computer science, or an engineering/science discipline with a software focus.
Experience developing command and control (C2) software for security or defence applications.
Familiarity with Geographic Information System (GIS) data and its manipulation.
Experience working with SQL databases.
Knowledge of user interface (UI) design and user experience (UX) best practices.
Understanding of real-time software development principles.
Experience with embedded Linux systems and embedded software development.
Exposure to machine learning techniques and classification methodologies.
Familiarity with Python or similar scripting languages.
Strong mathematical and statistical analysis skills.
Valid driver's licence and passport for occasional business travel related to projects

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.