Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and develop cutting-edge risk platforms using Java for a leading trading firm.
- Company: Join a top-tier investment firm with a focus on innovation and technology.
- Benefits: Competitive salary, health benefits, flexible work options, and opportunities for growth.
- Why this job: Make an impact in finance by building high-performance systems that drive real-time risk analytics.
- Qualifications: 3+ years in Java development, preferably in financial services or trading environments.
- Other info: Collaborative team culture with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a highly skilled Quantitative Software Developer to join our front office technology team focused on building and enhancing risk platforms for a leading trading or investment firm. The ideal candidate will have strong expertise in Java development and deep experience working within quantitative or risk-focused environments, particularly in designing, developing, and optimizing systems that support real-time and end-of-day risk calculations.
You will collaborate closely with quants, traders, and risk managers to develop scalable, high-performance platforms that process large datasets and support complex pricing and risk analytics across asset classes.
Key Responsibilities
- Design, develop, and maintain Java-based risk platform components that support pricing, market data integration, and risk analytics.
- Collaborate with quantitative analysts and model developers to integrate risk models into production systems.
- Build robust data pipelines and interfaces for market data, trade data, and risk sensitivities.
- Ensure low-latency and high-throughput performance across the platform.
- Participate in architectural decisions for the evolution of the risk platform, including microservices, cloud migration, or messaging integration.
- Support daily operations and participate in the on-call rotation for production risk systems.
- Write clean, testable, and well-documented code; contribute to CI/CD practices.
Required Qualifications
- Bachelor\’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 3+ years of experience in Java software development, ideally within financial services or a trading environment.
- Proven experience building or supporting risk platforms, pricing systems, or valuation engines.
- Strong knowledge of object-oriented programming, data structures, and design patterns.
- Familiarity with market risk, credit risk, or counterparty risk concepts.
- Experience with messaging systems (e.g., Solace, Kafka, or RabbitMQ) and distributed architecture.
- Solid understanding of multi-threaded and low-latency system design.
- Exposure to quant libraries, risk factor decomposition, or sensitivities is a strong plus.
Software Engineer employer: StreetID
Contact Detail:
StreetID Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and tech sectors. Attend meetups, webinars, or industry events where you can chat with quants and traders. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Java projects, especially those related to risk platforms or financial systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of risk concepts. Practice common algorithms and data structures, and be ready to discuss your experience with low-latency systems and messaging frameworks.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your experience with quantitative software development and risk platforms to catch our eye.
We think you need these skills to ace Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of a Software Engineer in a quantitative environment. Highlight your Java development experience and any relevant projects that showcase your skills in building risk platforms or working with large datasets.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with our needs. Mention specific experiences that demonstrate your expertise in financial services and risk analytics.
Showcase Your Technical Skills: Don’t forget to include your technical skills prominently. We want to see your proficiency in Java, as well as any experience with messaging systems or multi-threaded design. Be specific about the tools and technologies you've used!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at StreetID
✨Know Your Java Inside Out
Make sure you brush up on your Java skills before the interview. Be prepared to discuss your past projects and how you've used Java to solve complex problems, especially in risk platforms or trading environments.
✨Understand the Risk Landscape
Familiarise yourself with key concepts in market, credit, and counterparty risk. Being able to speak knowledgeably about these topics will show that you understand the environment you'll be working in and can contribute effectively from day one.
✨Showcase Your Collaboration Skills
Since you'll be working closely with quants, traders, and risk managers, be ready to share examples of how you've successfully collaborated in the past. Highlight any experiences where teamwork led to improved outcomes in your projects.
✨Prepare for Technical Challenges
Expect to face technical questions or coding challenges during the interview. Practice solving problems related to low-latency systems and multi-threaded design, as well as building data pipelines. This will help you demonstrate your problem-solving skills and technical expertise.
