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

JPMorgan Chase & Co.; Greater London; Presencial; GBP 100.000 - 150.000; Jornada completa

Descripción de la vacante

JPMorgan Chase & Co. is seeking a Lead Software Engineer for the AIML Data Platforms group in London. You will be a core technical contributor, building trusted, scalable tech products and guiding agile teams to secure, stable delivery.

Responsibilities include design, production code, code reviews, and AI-assisted engineering practices adoption. The role emphasizes responsible AI usage, cloud-native development, and collaboration with product managers to advance AI for data strategies.

Formación

• Hands-on experience delivering system design, application development, testing, and operational stability.
• Experience leading AI-assisted software development tools usage with code review and testing acceleration.
• Knowledge of secure, compliant AI adoption within delivery practices.

Responsabilidades

• 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

Conocimientos

Advanced Python

Containerization

AI-assisted tools

Responsible AI

SDLC proficiency

CI/CD

Cloud native

Herramientas

Graph databases (RDF - AWS Neptune)

Descripción del empleo

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