Lead Software Engineer - Java, Python, Cloud & AI

JP Morgan Chase · Glasgow, Scotland ·

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Overview

In this lead role, you will design and deliver trusted cloud financial management solutions within an agile, cross-functional environment. You will drive technical excellence and operational stability while collaborating to meet the firm’s business objectives. You’ll foster innovation and continuous improvement, shaping scalable, secure software that supports critical financial workflows. This is a high-impact opportunity to work with enterprise tools and AI-assisted engineering practices that accelerate delivery and quality.

Responsibilities

  • Invent and implement innovative software solutions and troubleshoot complex problems beyond conventional approaches
  • Develop secure, high-quality production code and review code from teammates
  • Champion and govern AI-assisted engineering practices to improve quality, speed, and reliability with standardized validation
  • Leverage SDLC tools, including AI-assisted development and automation, to maximize automation value
  • Identify and automate recurring issues to boost operational stability
  • Lead architectural evaluation sessions with external vendors, startups, and internal teams for integration suitability
  • Collaborate with cross-functional teams to align solutions with business goals
  • Promote software engineering, security, and resiliency best practices
  • Mentor and support the professional growth of team members

Key requirements

  • Formal training or certification on software engineering concepts and applicable experience as required by local guidance
  • Hands-on experience delivering system design, application development, testing, and operational stability
  • Advanced proficiency in Java, Python, Node.js, React, SQL
  • Experience leading the use of approved AI-assisted software development tools with ability to set expectations for AI output validation
  • Hands-on experience with enterprise-authorized AI-assisted development tools and ability to evaluate and refine AI outputs for correctness, performance, and security
  • Understanding of responsible AI use in engineering workflows, including data sensitivity and security considerations
  • Proficiency in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies (CI/CD, resiliency, security)
  • In-depth knowledge of the financial services industry and IT systems
  • Practical cloud native experience
  • Mentoring and coaching
  • Cross-functional collaboration
  • Security-minded thinking
  • Java
  • Python
  • Node.js
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