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Salary
$108k – $200k per year (Estimated)
Location
In office (Bournemouth)
Seniority
Staff
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.

As a Lead Software Engineer at JPMorganChase within our Commercial and Investment Bank, Payments Technology 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 delivering critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.

  • Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.

  • Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.

  • 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 communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.

  • 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.

  • Continuously update technologies and patterns to keep systems current.

  • Design and build solutions that avoid single points of failure using scalable architectural patterns.

  • Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and hands-on experience in software engineering, including system design, application development, testing, and operational support.

  • Proficiency in back-end technologies (e.g., Java, Python Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).

  • Demonstrated ability to independently solve design and functionality challenges with minimal supervision.

  • Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.

  • Hands-on experience designing and building scalable applications using SQL and NoSQL databases.

  • Understanding of application resiliency

  • 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

  • Proficiency in automation and continuous delivery methods.

  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.

  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

Preferred qualifications, capabilities, and skills

  • Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.

  • Strong problem-solving, analytical, and communication skills.

  • Ability to drive broader impact by sharing and contributing best practices.

  • Experience in the banking domain.

  • AWS certification.

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