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.

Your team

The team develops and operates the systems used to price and market-make FX Options electronically. It combines expertise in quantitative finance, software engineering, algorithmic trading and machine learning.
You will work in a high-performing quantitative development environment whose priorities are closely aligned with the front-office business. The team works iteratively, releases frequently and maintains direct ownership of its production systems.
The role offers exposure to the complete e-trading lifecycle, including market data, pricing models, automated quoting, execution, risk management, performance analysis and production monitoring. There is significant interaction with traders and with quantitative and technology teams in London, Zurich and Pune.

Your expertise

Essential experience
•  Strong server-side software development experience, preferably using Java, including concurrency and multithreaded systems.
•  Strong computer-science fundamentals, including data structures, algorithms, object-oriented design and distributed-systems principles.
•  Excellent analytical and problem-solving skills.
•  Experience building reliable, performance-sensitive production systems.
•  Strong understanding of the software development lifecycle, including automated testing, Git, continuous integration and continuous delivery.
•  Ability to take ownership of complex technical solutions from design through production deployment and support.
•  Strong communication skills and the ability to work closely with traders, quantitative researchers and engineering teams.
•  A degree in computer science, mathematics, statistics, physics, engineering, quantitative finance or another quantitative discipline.
Quantitative and AI experience
•  Practical experience implementing numerical, statistical or machine-learning models in production software.
•  Understanding of time-series modelling, statistical learning and model-validation techniques.
•  Awareness of the challenges involved in applying machine learning to financial markets, including low signal-to-noise ratios, non-stationarity, data leakage, overfitting, transaction costs and regime changes.
•  Ability to evaluate research critically and convert appropriate models into controlled, observable production services.
Desirable experience
•  Experience in electronic trading, market-making, derivatives or FX, particularly FX Options.
•  Knowledge of derivatives pricing, risk management or trading-system design.
•  Experience with messaging technologies and protocols such as FIX, Kafka, EMS, SBE or Aeron.
•  Familiarity with time-series databases, preferably KDB.
•  Experience with large-scale data or machine-learning infrastructure, GPU computing, reinforcement learning or sequential decision-making.
•  Experience designing low-latency or high-throughput distributed systems.

About us

UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.
We know that great work is never done alone. That’s why we place collaboration at the heart of everything we do. Because together, we’re more than ourselves. Want to find out more? Visit ubs.com/careers.

Join us

At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We’re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That’s why collaboration is at the heart of everything we do. Because together, we’re more than ourselves.
We’re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.

Disclaimer / Policy statements

UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.