Senior Python Engineer, Risk Platform - Hybrid (London)

Stanford Black Limited; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Stanford Black Limited in London seeks a Python Software Engineer to join the Risk Engineering team, building the next generation of a production-grade risk platform used by Risk Managers, Portfolio Managers, and Quant researchers.

You will help design and develop high-performance backend applications, contribute to architectural decisions, productionize quantitative models, and raise engineering standards across the platform in a collaborative, high-caliber team.

Qualifications

• 5+ years experience using Python.
• Strong Computer Science, Engineering or related academic background.
• Experience designing and building scalable APIs, distributed systems, and data pipelines.
• Experience working with SQL and backend services in high-performance production environments.
• Experience working in Agile engineering environments with a focus on software quality, scalability, and reliability.
• Market leading Compensation and Benefit packages.
• Working in a modern office in the heart of London, with the ability to work from home when required.

Responsibilities

• Design and develop high-performance, production-grade backend applications that power risk analytics and workflows.
• Contribute to architectural decisions and productionize quantitative models.
• Improve engineering standards across the risk platform and collaborate with Risk Managers, Portfolio Managers, and Quantitative Researchers.

Skills

Python

Distributed systems

APIs

SQL

Agile

Education

CS degree

Engineering or related field

Job description

Stanford Black Limited in London seeks a Python Software Engineer to join the Risk Engineering team, building the next generation of a production-grade risk platform used by Risk Managers, Portfolio Managers, and Quant researchers.

You will help design and develop high-performance backend applications, contribute to architectural decisions, productionize quantitative models, and raise engineering standards across the platform in a collaborative, high-caliber team.