AXQ Capital
Production Engineer
About this role
AXQ Capital, a global quantitative investment firm, seeks a Production Engineer to oversee live trading operations and production systems across global markets. You'll monitor algorithmic execution, respond to incidents, build automation tools, and ensure reliable operations supporting portfolio managers and researchers.
What you'll do
- Monitor live trading systems, portfolio risk, and compliance with trading limits in real-time
- Oversee pre-market preparation, algorithmic execution, and post-market processing workflows
- Investigate and resolve system outages, order issues, and trading anomalies with internal teams and external partners
- Build monitoring, alerting, dashboards, and automation tools to improve operational reliability
- Support deployment of new trading strategies and prepare for corporate actions and market events
- Conduct post-trade reconciliation and participate in incident reviews to continuously improve processes
What they're looking for
- Python programming and production-quality tool development
- Linux system administration
- Databases, networking, and distributed systems
- Financial market structure and trading systems knowledge
- Problem-solving and troubleshooting under pressure
- Monitoring and observability tools (Prometheus, Grafana, OpenTelemetry, ELK)
- CI/CD, containerization, and cloud infrastructure
- Risk management and trading operations
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AXQ Capital
AXQ Capital is a global quantitative investment firm that builds trading systems, backtesting frameworks, and risk management infrastructure across multiple asset classes and geographies. The company is hiring Quantitative Developers to work with research and engineering teams on core technology components and platform ownership.
View all jobs at AXQ CapitalLikely interview questions
- Describe your experience with production systems monitoring and incident response—how would you approach diagnosing a live trading system issue during market hours?
- Walk us through your experience with Python for building operational tools and automation. Can you share an example of a tool you built that improved efficiency?