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Position Overview We are looking for a Quant Developer to work on core backend systems for an algorithmic trading fund. The role involves building and operating services that process real-time data, integrate with external systems, and run continuously in production. This is a systems-focused engineering role where design quality, operational stability, and attention to detail matter. An understanding of financial markets can be a strong advantage, as it helps in reasoning about system behaviour, edge cases, and reliability requirements in live environments. Responsibilities Design and develop backend services that process real-time and event-driven data. Build and maintain scalable data pipelines for ingestion, transformation, and downstream consumption. Develop internal services and APIs that support platform workflows and operational needs. Work on systems that integrate with external services and counterparties. Translate high-level logic and requirements into reliable, production-grade software. Build execution-critical services with a strong focus on correctness, observability, and fault tolerance. Implement safeguards and controls within backend workflows to ensure predictable behaviour. Design systems that scale with increasing data volumes and account complexity. Monitor, maintain, and improve production systems, including incident response and post-incident fixes. Collaborate closely with engineering, research, and operations teams to evolve the platform. Required Technical Skills Strong proficiency in Python with experience building backend systems. Experience working with real-time or event-driven architectures. Solid understanding of asynchronous programming and concurrency. Experience building and integrating APIs (REST, WebSockets, or similar). Strong database fundamentals across relational and non-relational systems. Familiarity with message queues or streaming systems (Kafka, RabbitMQ, or similar). Experience designing systems for reliability, observability, and long-running production workloads. Comfort working in containerised and cloud-based environments. Good to Have Understanding of financial markets, particularly exchange-traded products and derivatives. Prior experience working on systems where correctness and uptime are critical. Exposure to market data, execution systems, or risk-aware workflows (from a systems perspective). Experience building internal platforms or tooling used by technical teams. Familiarity with Golang in performance-sensitive components. Skills: hft,python,financial markets,fastapi .
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In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.