AI (artificial intelligence) DevOps Engineer

Huxley Associates

City of London

1 month ago

Applications closed

Related Jobs

View all jobs

Senior Technology Specialist - AI

Data Engineer - AI Analytics and EdTech Developments

Senior Data Scientist (GenAI)

Senior Machine Learning Engineer

Data Scientist (Government)

Data Scientist Placement

AI (artificial intelligence) DevOps Engineer Azure Kubernetes Service (AKS),

Brilliant new opportunity for a AI DevOps Engineer with expertise in Azure Kubernetes Service (AKS), Helm, and KEDA to join a thriving STEM business who are heavily investigating in their AI (artificial intelligence) Platform including build a best in class AI (artificial intelligence) Platform with custom build of everything

Role details

Title : AI (artificial intelligence) DevOps Engineer
Location: can be based in either Glasgow or London City, 1 or 2 days a week in the office and home working hybrid
Permanent role- salary £70,000- 90,000

Technical stack: Azure Kubernetes Service (AKS), Helm, and KEDA, Azure services, Semantic Kernel agents, Kubernetes clusters, Azure API. API Gateway, Azure API Management (APIM), Azure Application Gateway

About the job

An exciting opportunity for a talented AI DevOps Engineer, you will focused on looking at areas where AI can add improvements, as everything is being custom built rather than off the shelf

We do have other artificial intelligence roles in the team including AI (artificial intelligence) test Engineer roles, so please do send through a CV still if that is more in line with your expectations

AI Security Engineer
...

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.