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Salary
≈ $101k – $188k per year (Estimated)
Location
In office (Glasgow)
Seniority
Staff

Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 24, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. Join us to shape market-leading technology products that power the future of financial services. You’ll collaborate with talented colleagues, grow your skills, and make a real difference for our clients and communities. At JPMorganChase, your ideas and expertise are valued, and your growth is our priority.

As a Lead Software Engineer in Corporate Technology, you will play a key role on an agile team dedicated to building secure, stable, and scalable technology solutions. You will contribute your technical expertise across multiple areas, supporting the firm’s business objectives. You’ll help drive innovation, mentor others, and ensure our products meet the highest standards. Your leadership will help shape the team’s culture and success.

Job 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 to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of effective patterns
  • Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to maximize automation value
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability
  • Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability for existing systems

Required Qualifications, Capabilities, and Skills:

  • Formal training or certification on software engineering concepts and applied experience (follow local country guidance as applicable)
  • Hands-on experience delivering system design, application development, testing, and operational stability
  • Advanced proficiency in one or more programming languages
  • Demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption
  • 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 IT systems
  • Practical cloud native experience

Preferred Qualifications, Capabilities, and Skills:

  • Experience mentoring and developing engineering talent
  • Familiarity with modern DevOps practices and tools
  • Exposure to large-scale distributed systems
  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration abilities
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