Senior Lead Software Engineer - AI-Driven, Secure Cloud

JPMorgan Chase & Co.

Greater London

On-site

GBP 110,000 - 150,000

Full time

14 days+

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Job summary

JPMorganChase & Co. is seeking a Lead Software Engineer within the [insert LOB or sub LOB] to join an agile team that enhances, builds, and delivers trusted market-leading technology products in a secure, scalable way.

As a core technical contributor, you will drive critical technology solutions across multiple areas to support the firm’s objectives. The role focuses on designing and delivering secure, production-ready software, leading AI-assisted development practices, and ensuring robust

Qualifications

Formal training or certification on software engineering concepts and 5+ years applied experience (NAMR/APAC – India/ LATAM/ Hong Kong)
Formal training or certification on software engineering concepts and advanced applied experience (EMEA/LATAM-Brazil)
Singapore follow local country guidance
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)
Demonstrated experience leading effective use of approved AI-assisted software development tools 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
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience

Responsibilities

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine approaches
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 to improve code quality, delivery speed, and outcomes, with validation standards
Applies knowledge of tools within the SDLC toolchain, including AI-assisted development and automation capabilities
Identifies opportunities to eliminate or automate remediation of recurring issues to improve stability
Leads evaluation sessions with external vendors, startups, and internal teams to assess designs and applicability within existing systems