Python Full-Stack Engineer: Data Pipelines & AI Tools

J.P. MORGAN; Greater London; On-site; GBP 70,000 - 105,000; Full time

Job summary

J.P. Morgan is seeking a Software Engineer for Model Risk Governance & Review to develop tools for MRGR analytics, improving efficiency and reducing duplication of effort across governance and testing activities.

You will build data pipelines, integrate model monitoring, and collaborate with cross-functional teams to leverage LLM capabilities while maintaining strong data controls and secure coding practices.

Qualifications

• Formal training or certification on software engineering concepts and advanced applied experience.
• Degree in STEM with programming exposure.
• Proficient in Python with Tornado, TypeScript, and React knowledge.
• Strong communication and risk-management mindset.
• Experience with enterprise AI-assisted development tools.

Responsibilities

• Build data pipelines to fetch, validate, transform, and deliver data to applications, enabling reliable downstream analytics, automation, and reporting.
• Integrate on-going performance monitoring requirements for models into business applications through applied development work, primarily in Python using in-house frameworks.
• Leverage developer productivity tools to accelerate delivery, improve code quality, and enhance documentation and testing.
• Collaborate with cross-functional teams to identify opportunities for LLM integration and develop solutions that leverage LLM capabilities.
• Build intelligent solutions to support MRGR staff activities, including workflow automation and insight generation.

Skills

Python

Communication

Critical thinking

Risk mindset

Education

Bachelor's or Master's degree in STEM

Tools

Tornado web framework

TypeScript

React

Software architecture

OO design patterns

Job description

J.P. Morgan is seeking a Software Engineer for Model Risk Governance & Review to develop tools for MRGR analytics, improving efficiency and reducing duplication of effort across governance and testing activities.

You will build data pipelines, integrate model monitoring, and collaborate with cross-functional teams to leverage LLM capabilities while maintaining strong data controls and secure coding practices.