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Lead Software Engineer – AIML Data Platform (Data, Python, Containers/Kubernetes)

JPMorgan· LONDON, LONDON, United Kingdom· £73,500–£99,750/yr (est.)Licensed sponsor
Posted 18 Sept 2026 · Added 18 Sept 2026, 12:22
JPMorgan3.9 (20,432)10,000+ employees

Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.

Levels.fyi · global compSWE $164k TC ($122k–$205k)
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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 AMDP (AIML Data Platforms), 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

Works closely with product managers and data strategy professionals to advance the firm’s agenda in AI for Data

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.

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

Mentors more junior engineers in the team

Required qualifications, capabilities, and skills

Hands-on practical experience delivering system design, application development, testing, and operational stability

Advanced Python Architecture and Development skills. Must also be familiar with developing solutions in a containerized environment

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

Practical cloud native experience

Preferred qualifications, capabilities, and skills

Any background in graph databases (especially RDF stores like AWS Neptune)

Working familiarity with Gen AI Engineering tools/frameworks - capable of designing / building pipelines