Front-Office CRB Engineer & AI Researcher

UBS; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

UBS in London is seeking an engineer/researcher to join the CRB desk within UBS Global Markets. This front-office role blends software engineering, data science, quantitative research and trading technology.

You will collaborate with traders and quants to develop AI capabilities, analytics platforms and production systems used daily, handling large datasets, CI/CD pipelines and scalable infrastructure.

Qualifications

• Curious about applying AI to improve workflows with sound judgment.
• Strong problem-solving and analytical skills.
• Proactive, ownership mindset and quick learner.
• Excellent Python and production-quality coding.
• Extensive experience in Linux/Unix environments.
• Experience building production software with CI/CD and DevOps practices.
• Strong communication and cross-team collaboration.

Responsibilities

• Develop, maintain, and enhance front-office applications, automation frameworks, and trading tools.
• Build and manage the desk's AI tooling and analytics platforms.
• Apply data science and statistical techniques to improve decision-making and analytics.
• Design, implement, and maintain production-grade software used daily.
• Work with large datasets to generate insights and improve efficiency.
• Develop monitoring, reporting, and operational tooling for automated trading and market-making systems.
• Collaborate with traders, quants, and developers to solve business and technical problems.

Skills

Python

Linux/Unix

CI/CD

Data science

AI/ML/LLM

Front-office app development

Collaboration

Tools

KDB+/q

Job description

UBS in London is seeking an engineer/researcher to join the CRB desk within UBS Global Markets. This front-office role blends software engineering, data science, quantitative research and trading technology.

You will collaborate with traders and quants to develop AI capabilities, analytics platforms and production systems used daily, handling large datasets, CI/CD pipelines and scalable infrastructure.