Private Cloud Software Engineer III

JPMorgan Chase & Co.
Glasgow
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Data Science Engineer

Machine Learning Engineer

Machine Learning Engineer Bristol (GB) Professionals

Artificial Intelligence and Machine Learning Graduate

Machine Learning Team Lead

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Private Cloud Software Engineer III at JPMorgan Chase within the Core & Foundational Cloud Platforms, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Contributes to software engineering communities of practice and events that explore new and emerging technologies Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and applied experience Hands-on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages such as Java, C#, Python, Golang or equivalent language Proficiency in automation and continuous delivery methods, availability, scalability, and cost transparency.  Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (., cloud, artificial intelligence, machine learning, mobile, In-depth knowledge of the financial services industry and their IT systems,  Practical experience in cloud native, virtualization, APIs, Terraform, PowerShell, Ansible, Infrastructure-as-code. 

Preferred qualifications, capabilities, and skills

Familiarity with modern front-end technologies Exposure to cloud technologies

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.

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.