Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Private Cloud Software Engineer III

JPMorgan Chase & Co.
Glasgow
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer (Large Systems) London, UK

Machine Learning Engineer (Large Systems) Bristol, UK

Machine Learning Engineer

Machine Learning Engineer (Large Systems)

Sr. Machine Learning Engineer

Machine Learning Engineer – AI for Grid Innovation & Energy Transition

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.