Full-Stack Engineer II: AI‑Enhanced, Secure & Scalable

JPMorgan Chase & Co.

Glasgow

On-site

GBP 55,000 - 90,000

Full time

14 days+

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Job summary

JPMorgan Chase & Co. in the United Kingdom (Glasgow) invites applications for Software Engineer II as part of the Payments Technology team. You will join an agile group delivering secure, scalable software components across the firm's technology products.

The role focuses on design, development, and troubleshooting across multiple components, using secure coding practices and modern languages. You will work within SDLC, CI/CD, and AI-assisted tooling, contributing to resilient, audited systems.

Qualifications

Formal training or certification on software engineering concepts and expanding applied experience.
Hands-on practical experience in system design, application development, testing, and operational stability.
Experience developing, debugging, and maintaining code in a large-scale environment using one or more modern programming languages and database querying languages.
Demonstrable ability to code in one or more languages.
Experience across the full Software Development Life Cycle.
Exposure to agile methodologies such as CI/CD, application resiliency, and security practices.
Emerging knowledge of software applications within a technical discipline (e.g., cloud, AI/ML, mobile).
Hands-on experience using enterprise-approved AI-assisted software development tools with ability to evaluate AI outputs.
Understanding of responsible AI use in engineering workflows, including data sensitivity and security.

Responsibilities

Execute standard software solutions through design, development, and technical troubleshooting across multiple system components.
Write secure, high-quality code using at least one programming language with limited guidance.
Design, develop, and troubleshoot with consideration of upstream and downstream systems and their implications.
Apply troubleshooting skills to solve basic technical problems.
Analyze large data sets to identify problems and aid decision-making in secure, stable app development.
Learn and apply SDLC processes and best practices for secure, stable code and systems.
Contribute to a team culture of diversity, inclusion, and respect.
Leverage AI coding assist tools to improve code quality, delivery speed, and productivity with peer review and testing.
Applies knowledge of tools within the SDLC toolchain, including AI-assisted development and automation capabilities.