AI Quant Developer, FX Options E-Trading

We are looking for an experienced AI Quant Developer to join the FX Options E-Trading team within UBS Investment Banking. This is a senior, hands-on quantitative development role focused on designing, building and operating the next generation of algorithmic pricing, market-making, execution and automated risk-management capabilities. The role combines strong software engineering with quantitative modelling and applied machine learning. You will turn quantitative and AI research into robust production systems. This includes working from initial analysis and prototyping through model validation, software design, implementation, deployment, real-time monitoring and production support. You will work closely with traders, quantitative analysts and engineering teams, but your primary responsibility will be the technical design and delivery of scalable, reliable e-trading solutions. Quantitative software development •  Design and implement high-performance systems for electronic FX Options pricing, market-making, execution and risk management. •  Build robust server-side applications and services, with particular attention to concurrency, latency, availability and operational resilience. •  Develop reusable quantitative components, analytics and infrastructure that allow new models and trading ideas to be evaluated and deployed efficiently. •  Take ownership of solutions across the full software development lifecycle, from requirements analysis and architecture through implementation, testing, release and production support. •  Maintain high engineering standards through automated testing, code review, observability, controlled releases and continuous improvement. AI and quantitative model implementation •  Translate quantitative research and machine-learning prototypes into maintainable, production-quality software. •  Develop and integrate statistical-learning, time-series and machine-learning models for pricing, quoting, execution, liquidity management and automated risk management. •  Build data and research pipelines for analysing large-scale market, trading and client datasets. •  Implement robust feature engineering, model evaluation and back-testing frameworks. •  Ensure that models can be monitored appropriately in production, including performance, model drift and changing market regimes. Production platform ownership •  Develop and enhance systems supporting electronic market-making, with a strong focus on reliability, performance and scalability. •  Improve the platform architecture so that models can move safely and efficiently from research into live trading. •  Diagnose complex production and performance issues across applications, data pipelines and distributed services. •  Contribute to the team’s continuous delivery practices, enabling frequent, controlled production releases. •  Drive improvements that have a measurable impact on automation, trading performance, revenue generation and business growth. Technical leadership •  Provide technical direction on quantitative development, AI engineering and e-trading architecture. •  Identify opportunities to apply machine learning and modern software-engineering techniques to existing trading workflows. •  Challenge modelling and engineering assumptions, helping the team select solutions that are empirically sound and operationally robust. •  Mentor quantitative developers and contribute to engineering standards, design reviews and technical strategy. •  Collaborate closely with traders, quantitative researchers and global technology teams to deliver new trading capabilities.