QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.
Why this role stands out
This Senior AI Engineer role at Qube Research & Technologies offers an exceptional opportunity to drive AI adoption within a cutting-edge HFT environment, enabling you to build impactful AI-powered tools and platforms. You'll thrive here if you possess strong Python software engineering skills and experience with modern AI platforms, eager to collaborate and contribute to a culture of innovation.
Quick overview
Job description
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT
- Build and maintain AI-powered applications, assistants, and agentic workflows
- Develop integrations between AI systems and internal tools, repositories, databases, and knowledge sources
- Design and implement AI agents capable of interacting with enterprise systems and APIs
- Evaluate new models, frameworks, and AI tooling
-
Partner with researchers, engineers, and business teams to identify high-value use cases
- Contribute to standards and best practices for AI development across the HFT business
Your present skillset
- Strong software engineering experience in Python
- Experience building and operating production systems
- Excellent design, debugging, and problem-solving skills
- Experience with modern AI platforms, LLMs, and AI tooling.
- Strong understanding of APIs, distributed systems, and software architecture
- Ability to independently drive projects from conception to production
- Experience building AI agents or agentic workflows
- Experience evaluating AI systems and coding assistants
- Familiarity with MCPs, tool-use frameworks, or related technologies
- Experience with quantitative research, trading technology, or financial markets (good-to-have)
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