Quant Research Engineer

About the role

The Quant Research Engineer will design, build and maintain core quantitative pipelines, data infrastructure and compute environments that power research and trading activities. The role blends high‑performance engineering with AI‑augmented tooling to accelerate the research workflow.

Key responsibilities

• Own the design, implementation and reliability of the firm’s data and compute platform, including AI‑native capabilities such as LLM services and retrieval infrastructure.
• Collaborate with quantitative researchers and development teams to integrate new components, enforce system design standards, and embed AI tools that streamline literature ingestion, data exploration and signal prototyping.
• Manage deployment, monitoring and operational health of production and research systems, applying AI‑assisted observability, automated log analysis and anomaly detection.
• Drive infrastructure‑as‑code practices, automate workflows and leverage AI coding agents to improve velocity and quality.

Required profile

• 3–5 years of experience in quantitative development or fast‑paced startup engineering, with end‑to‑end ownership of trading, research or AI infrastructure.
• Top‑tier academic background (PhD preferred) in Computer Science, Engineering, Physics, Mathematics or Statistics.
• Demonstrated passion for AI, preferably with experience building LLM‑powered tools for research or engineering.

Required skills

• Strong proficiency in modern C++ and Python for high‑performance computing.
• Experience with large‑scale data infrastructure (real‑time/streaming tick data) and cloud platforms (AWS, GCP or Azure).
• Knowledge of databases and processing frameworks: KDB+, Apache Spark, Dask, Redis, SQL, NoSQL, distributed file systems.
• Containerization and orchestration: Docker, Kubernetes.
• DevOps tools: Terraform, CloudFormation, CI/CD pipelines (GitHub Actions, GitLab CI), observability tooling.
• Practical use of LLM APIs, agentic workflows, retrieval‑augmented generation and structured output pipelines.