Senior Java Software Engineer

Ascendion
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Simulation Engineer (Data Science)

Senior Data Scientist

Senior Machine Learning Engineer, Search & Recommendations

Data Lead - Artificial Intelligence & Automation (12 Month Fixed-Term Contract)

Senior Machine Learning Research Engineer

Senior Data Scientist

Position Details:


Job Title:Senior Java Developer

Location:London (hybrid)


Job Description

We are seeking a highly skilled and motivated Java Developer with hands-on expertise inAzure DevOps, Spring Boot, AKS, AgroCD, ACR, Kubernetes, ADO etc. The ideal candidate will play a key role in designing, developing, deploying, and maintaining enterprise-grade applications while leveraging cloud-native solutions and CI/CD practices on Azure. Candidates with experience in the banking domain will be given preference.


About Us:

Ascendion is a global, leading provider of AI-first software engineering services, delivering transformative solutions across North America, APAC, and Europe. We are headquartered in New Jersey. We combine technology and talent to deliver tech debt relief, improve engineering productivity solutions, and accelerate time to value, driving our clients’ digital journeys with efficiency and velocity. Guided by our “Engineering to the power of AI” [EngineeringAI] methodology, we integrate AI into software engineering, enterprise operations, and talent orchestration, to address critical challenges of trust, speed, and capital. For more information, please go towww.ascendion.com

With Ascendion (www.ascendion.com), you:

  • Will get to work on numerous challenging and exciting projects on our various offerings including Salesforce, AI/Data Science, Generative AI/ML, Automation, Cloud Enterprise and Product/Platform Engineering.
  • At Ascendion you have high chances of project extension or redeployment to other clients.
  • Additionally, you can also share CV of anyone you know. We have a referral policy in place.

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.