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Salary
≈ $121k – $245k per year (Estimated)
Location
In office (Chicago)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Oct 6, 2026. Chase UK scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Chase UK is the digital retail bank launched in the United Kingdom by JPMorgan Chase, offering app-based current and saver accounts, cashback on card spending and investing through JP Morgan Personal Investing, with its registered office at Canary Wharf in London. It launched in 2021 as the first international expansion of the Chase consumer banking brand, has no physical branches and provides round-the-clock support through its app and by phone. Its London-based teams include software engineers, product managers, data scientists, designers and customer service staff, and the bank bought the digital wealth manager Nutmeg in 2021.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
  • Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience
  • Experience implementing solutions using Java, SQL, UI frameworks, Design patterns, microservices, Cloud native architecture, Angular/React, RESTful APIs for enterprise-scale applications.
  • Experience with SQL performance tuning, JDBC, and ORM frameworks (Hibernate/JPA)
  • Strong experience in various SQL and NoSQL datastores including Oracle, MongoDB
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) 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 considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Proficiency in unit testing frameworks such as JUnit and Mockito for ensuring code quality.
  • Deep knowledge of messaging platforms such as Apache Kafka

Preferred qualifications, capabilities, and skills

  • Familiarity with DevOps practices, containerization and orchestration
  • Exposure to AI systems such as Copilot, Claude
  • Exposure to AWS technology stack
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