Lead Backend Engineer – Cloud Microservices & AI-Driven

JPMorgan Chase & Co.

Greater London

On-site

GBP 90,000 - 130,000

Full time

4 days ago

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Job summary

JPMorgan Chase & Co. invites experienced engineers to join the International Consumer Bank as a Lead Software Engineer. You will deliver cloud-native microservices, model domains, and secure software while guiding teams across distributed environments.

You will champion AI-assisted development tools and ensure reliable, scalable systems in a regulated financial landscape. You will collaborate with product teams to evolve architectures, maintain code quality, and ensure production readiness

Qualifications

Formal training or certification in software engineering concepts and applied experience.
Recent hands-on professional experience as a back-end software engineer.
Experience in coding in Java.
Experience designing and implementing effective tests (unit, component, integration, end-to-end, performance, etc.).
Excellent written and verbal communication skills in English.
Experience with cloud technologies and distributed systems, RESTful APIs and web technologies.
Knowledge of messaging frameworks.
Experience operating, supporting and securing mission critical software applications.
Understanding of different data stores (relational).
Coach team members on coding practices, design principles, and implementation patterns.
Manage stakeholders and prioritize work across multiple streams.
Experience leading use of approved AI-assisted development tools with validated outputs.
Strong understanding of responsible AI use in engineering workflows.

Responsibilities

Deliver end-to-end cloud-native microservices architecture solutions using the latest technologies.
Use domain modeling to build best-in-class business products.
Structure software for testability and ease of evolution.
Build scalable architectures with no single points of failure.
Develop secure code protecting customers and systems.
Investigate and fix issues promptly and prevent recurrence.
Ensure releases occur with zero downtime for users.
Handle data read/write optimized for business needs.
Monitor performance and optimize where appropriate.
Keep systems reliable and operable, updating patterns as needed.
Support products through their lifecycle including incident management.
Promote enterprise AI-assisted engineering practices with validated standards.