Lead Java Cloud Engineer — AI-Driven on AWS & Databricks

JP Morgan Chase

Glasgow

On-site

GBP 90,000 - 150,000

Full time

14 days+

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Job summary

JPMorganChase in Glasgow seeks a Lead Software Engineer to drive delivery of trusted, scalable technology within Corporate Technology. You will work in an agile team, shaping architecture, code quality, and security practices to support critical firm objectives.

You will mentor peers, contribute to AI-assisted development practices, and collaborate across business lines to deliver resilient, high-performance systems in a dynamic financial services environment.

Qualifications

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.
Advanced in one or more programming languages, preferrably Java.
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Proficient in all aspects of the Software Development Life Cycle.
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
In-depth knowledge of the financial services industry and their IT systems.
Practical cloud native experience.

Responsibilities

Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine approaches to solve complex problems.
Develop secure, high-quality production code, and review and debug code written by others.
Drive team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of effective patterns across the team.
Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.