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

Apply Now

Cloud Platform Engineer - Senior Lead Software Engineer - London

241387-Comp & Ben Admin Prof Fees
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Staff Data Scientist

Staff Data Scientist

MLOps Platform Engineer

MLOps Platform Engineer

Cloud Engineer

Description Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer in the Cloud Foundational Services division of JPMorgan Chase, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications Job responsibilities Enable a friction free experience for 35,000 software engineers: as close to native as possible whilst meeting the stringent/best in class/security & controls requirements for financial institution. Collaborate with application developers across a diverse range of businesses and use cases balancing the need to modernize with the need to migrate Develops secure and high-quality production code, and reviews and debugs code written by others Drives decisions that influence the product design, application functionality, and technical operations and processes Serves as a function-wide subject matter expert in one or more areas of focus Contributes actively to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle Influences peers and project decision-makers to consider the use and application of leading-edge technologies Adds to the team culture of diversity, equity, inclusion, and respect Empower the at-scale migration of a diverse and complex business with use cases ranging from simply needing a place to run a container through to sophisticated power users, and multi-tenant platforms. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Experience with technologies including EC2, ECS Fargate, Lambda & Step Functions Advanced in one or more programming language(s) Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Experience with AWS and Terraform Preferred qualifications, capabilities, and skills Ability to tackle design and functionality problems independently with little to no oversight Practical cloud native experience

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.