Design Manager

Sphere Solutions Ltd
Exeter
10 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Manager

Data Scientist-Manager

Machine Learning Engineer (Manager)

Data Science Lead / Manager

Data Scientist-Senior Manager

Sr Product Manager, Data Science

Design Manager

Exeter


Sphere Solutions are working with a one of the region’s leading contractors, recruiting for a Design Manager to work with a highly experienced delivery team. Projects will be varied, covering all aspects of construction, including industrial, commercial and education- ranging from £1m up to £10m, design and build projects, with an excellent secured workload and forward programme of works this is a great opportunity.


The role:

  • Lead, manage and chair design meetings with external consultants and management teams
  • Interface between the client, design teams (external consultants) and operational teams
  • Manage design change and reports
  • Liaison with the commercial team, relay any implications of changes to the client
  • Assisting the Estimator with design change / price implications, pre-construction assistance regarding design change


The Candidate:

  • Demonstrable pre / post contract experience in Design Management
  • Have worked with a regional / main contractor in a similar role
  • Longevity with previous employers
  • Good client liaison skills, approachable and a good problem solver


On offer is an excellent salary and package, including car/allowance, company pension, life assurance and private medical insurance.


To Apply: For an informal discussion please call Abbie Evans on or apply as instructed.


Sphere Solutions are one of the South West & Wales market leaders in providing recruitment services to the built environment.


With specialist consultants based in our regional offices (Bristol, Cardiff, Plymouth and St Austell) we fill vacancies daily with contractors, developers, civil engineers and their supply chain in high volume with quality candidates.

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.