Lead Software Engineer in JPMorganChase's AI & ML Data Platforms team, based in Glasgow, United Kingdom. This on-site role focuses on leading complex engineering challenges, delivering secure and scalable software, and advancing AI-enabled development practices across the software lifecycle.

Responsibilities

Qualifications:

Provide technical guidance to business units, engineering teams, contractors, and vendors.
Develop secure, high-quality production code; review and debug code written by others.
Drive product design decisions, application functionality, and operational processes.
Act as a subject-matter expert, sharing knowledge and best practices across the engineering community.
Contribute to enterprise-wide frameworks, tools, and SDLC practices; advocate for AI-assisted engineering.
Promote a culture of diversity, inclusion, and respectful collaboration.
Lead the adoption of AI-assisted development techniques to improve code quality, delivery speed, and operational outcomes, while ensuring secure coding, peer review, automated testing, and pattern reuse.
Apply SDLC tooling and AI-enabled automation to maximize value delivered by software.
Formal training or certification in software engineering; substantial practical experience in system design, application development, testing, and operations.
Proficiency in one or more programming languages with a strong focus on code quality and maintainability.
Deep knowledge of cloud, AI/ML, mobile, and related technologies.
Ability to work independently with minimal oversight.
Hands-on cloud-native e

About the role

Lead Software Engineer in JPMorganChase's AI & ML Data Platforms team, based in Glasgow, United Kingdom. This on-site role focuses on leading complex engineering challenges, delivering secure and scalable software, and advancing AI-enabled development practices across the software lifecycle.

Responsibilities

Qualifications:

Provide technical guidance to business units, engineering teams, contractors, and vendors.
Develop secure, high-quality production code; review and debug code written by others.
Drive product design decisions, application functionality, and operational processes.
Act as a subject-matter expert, sharing knowledge and best practices across the engineering community.
Contribute to enterprise-wide frameworks, tools, and SDLC practices; advocate for AI-assisted engineering.
Promote a culture of diversity, inclusion, and respectful collaboration.
Lead the adoption of AI-assisted development techniques to improve code quality, delivery speed, and operational outcomes, while ensuring secure coding, peer review, automated testing, and pattern reuse.
Apply SDLC tooling and AI-enabled automation to maximize value delivered by software.
Formal training or certification in software engineering; substantial practical experience in system design, application development, testing, and operations.
Proficiency in one or more programming languages with a strong focus on code quality and maintainability.
Deep knowledge of cloud, AI/ML, mobile, and related technologies.
Ability to work independently with minimal oversight.
Hands-on cloud-native e

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