We are looking for a Quantitative Developer to join the Core Engineering team to help build out our Quantitative Execution Services. You will be closely working with researchers and traders on the Central Execution Desk, directly contributing to scale up our Mid-Frequency Trading capabilities. This role sits at the intersection of research and engineering—ideal for someone who has prior experience with execution algorithms and quantitative trading systems, and can translate research ideas into robust, high‑performance production software.

Responsibilities

• Design, implement, and maintain high performance services in Rust and Python for our execution desk, including algo wheel, smart order routers, internalisers, etc.
• Partner closely with our quantitative researchers to take research prototypes to production: refactoring, adding tests, telemetry, SLIs/SLOs, and CI/CD automation.
• Write robust pipelines for market‑data ingestion, model training/inference, and post‑trade analytics.
• Optimize for reliability and performance (throughput, tail‑latency, memory footprint) on distributed systems running in production trading environments.
• Establish best practices in code quality, observability, and on‑call readiness; write clear documentation to enable effective collaboration across research and engineering.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related STEM field.
• 2–5 years of professional software‑engineering experience, including production systems written in Python or Rust.
• Proficiency in a systems language—Rust preferred (C++/Go also acceptable)—and a desire to deepen that expertise.
• Strong CS fundamentals: algorithms, data structures, concurrency, networking, and performance profiling.
• Experience with real‑time and/or historical market data, or other high volume time series data.
• Familiarity with SQL and at least one columnar/time‑series store (e.g., kdb+, ClickHouse, InfluxDB, Parquet/Arrow).
• Proficiency with Linux development, Git, containers, and CI/CD workflows.
• Excellent problem‑solving abilities, attention to detail, and clear communication skills

Nice to Have

• Hands‑on exposure to execution algos, TCA, order routing, or market‑impact modeling.
• Understanding of broker and exchange order entry APIs, and FIX/native protocols.
• Experience building distributed systems with message buses (Kafka, ZeroMQ) and asynchronous I/O (e.g. tokio)
• Knowledge of statistical/ML libraries and tooling (NumPy, pandas, scikit‑learn, PyTorch); experience shipping inference in production.
• Experience with cloud or on‑prem orchestration and scheduling (Kubernetes, Ray, HTCondor, SLURM).