Lead Cloud Platform Engineer – Multi-Cloud Foundations

JPMorganChase

Glasgow

On-site

GBP 90,000 - 125,000

Full time

6 days ago
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Job summary

J.P. Morgan is seeking a Lead Software Engineer to shape cloud foundation services across AWS, Azure, and Google Cloud. You will join an agile team delivering secure, scalable platform tooling and provider-agnostic designs for multi-cloud ecosystems.

You will own significant technical design decisions, mentor engineers, and drive adoption of enterprise AI-assisted development practices within the SDLC while ensuring reliability and security across production platforms.

Qualifications

  • Formal training or certification in software engineering concepts and advanced applied experience.
  • Advanced proficiency in Java, Python, or Go.
  • Hands-on experience with at least one major public cloud.
  • Experience designing, developing, and maintaining production software systems.

Responsibilities

  • Develop secure, high-quality production code for cloud platform services and tooling.
  • Own technical design decisions and contribute to architecture and processes.
  • Build deep platform knowledge and share it across the team.
  • Mentor engineers and raise engineering practices.
  • Contribute to engineering community through firmwide frameworks and tools.
  • Influence peers on leading-edge technologies and decisions.
  • Drive adoption of AI-assisted engineering practices with secure validation.
  • Utilize SDLC tools to improve automation and code quality.

Skills

Java
Python
Go
Cloud experience
Mentoring
SDLC

Education

Formal training or certification in software engineering

Tools

Terraform
AI-assisted development tools

Job description

J.P. Morgan is seeking a Lead Software Engineer to shape cloud foundation services across AWS, Azure, and Google Cloud. You will join an agile team delivering secure, scalable platform tooling and provider-agnostic designs for multi-cloud ecosystems.

You will own significant technical design decisions, mentor engineers, and drive adoption of enterprise AI-assisted development practices within the SDLC while ensuring reliability and security across production platforms.

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