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Salary
≈ $130k – $263k per year (Estimated)
Location
In office (Jersey City)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Oct 9, 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 JPMorganChase within the the Asset & Wealth Management Client Information team, you are 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 breakdown technical problems
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • 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.
  • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.
  • Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  • Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience using enterprise-authorized AI-assisted software development tools to be used for for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one or more programming language(s) : Java or Python
  • Experience coding in Front end technology including React
  • Experience with Cloud technology including AWS
  • 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
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Strong communication and collaboration skills globally and mentor junior engineers on team.

Preferred qualifications, capabilities, and skills

  • In-depth knowledge of the financial services industry and their IT systems

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