Quant Research Engineer

About the Role

We are seeking an experienced Quant Research Engineer to design, develop, and maintain the core quantitative research infrastructure critical to our trading and research operations in Dubai. The ideal candidate will have a strong academic background, preferably PhD-level training, with expertise in AI and quantitative systems engineering, and a passion for integrating advanced AI capabilities such as large language models into research workflows.

Key Responsibilities

• Design, develop, and sustain the firm's essential quantitative data and computing pipelines for both research and production systems.
• Ensure high availability, scalability, and performance of systems vital to trading and research operations.
• Lead the architectural design and vision for next-generation data and compute platforms incorporating AI-native features like LLM services, agent-based workflows, and retrieval infrastructure.
• Collaborate closely with Quantitative Researchers and engineering teams to grasp requirements and embed new components into core infrastructure.
• Serve as a key technical expert ensuring smooth data and computation flow across various teams and systems.
• Identify opportunities to leverage AI for enhancing the research cycle from literature review to signal development, and build the necessary tools for routine use.
• Establish and maintain strict standards for system architecture, code quality, testing, and deployment procedures.
• Oversee deployment, monitoring, and operational health of both production and research infrastructures.
• Implement extensive observability, logging, and alert systems while employing AI-driven methods such as automated log analysis and anomaly detection for superior reliability.
• Promote infrastructure-as-code and automate operational workflows utilizing AI coding assistants and LLM utilities when they improve efficiency and quality.

Qualifications and Experience

• 3 to 5 years of professional experience in a quantitative development position involving building and maintaining quantitative research and production pipelines, or significant engineering exposure in dynamic startups with strong AI/LLM engineering experience.
• Proven leadership and ownership of critical trading, research, high-performance computing, or AI infrastructure components.
• Advanced proficiency in modern C++ and Python within high-performance computing contexts.
• Experience handling large-scale data infrastructure, including real-time streaming and historical tick data.
• Strong foundation in cloud platforms such as AWS, GCP, or Azure and knowledge of parallel computing frameworks.

Technical Skills

• Comprehensive understanding of technology stack relevant to quantitative research, with ability to choose optimal tools (e.g., KDB+, Apache Spark, Dask, Redis).
• Hands-on experience with LLM applications, agentic workflows, including APIs, frameworks, retrieval-augmented generation, and structured output pipelines, with sound judgment on AI applicability.
• Expertise in database systems including SQL, NoSQL, and distributed file storage architectures.
• Familiarity with containerization (Docker) and orchestration platforms (Kubernetes).
• In-depth experience with DevOps practices including infrastructure-as-code tools like Terraform or CloudFormation, CI/CD pipelines such as GitHub Actions or GitLab CI, and system observability tools enhanced by AI.

Soft Skills

• Strong analytical and critical thinking skills to decompose complex challenges into elegant solutions.
• Collaborative mindset to build productive partnerships and operate effectively in team environments.
• High integrity and ownership, ensuring ethical management of sensitive data and models.
• Continuous learner eager to embrace emerging AI technologies and integrate them into work processes.
• Excellent communication skills to explain intricate technical matters to diverse audiences.

Preferred Academic and Competitive Credentials

• Top-tier academic qualifications from globally renowned universities (MIT, Harvard, Stanford, Caltech, Princeton).
• PhD training in Computer Science, Engineering, Physics, Mathematics, or Statistics is highly desirable.
• Gold medals in national or international competitions (IMO, CMO, IOI, NOI, IPhO, CPhO) are strongly preferred.
• Experience at elite quantitative trading firms or leading AI/technology companies is advantageous.

Additional Information

Please submit your resume referencing REQ-30162 to the appropriate contact. The position is located in Dubai and requires onsite presence.