Support Engineer

Overview

• Provide technical support for proprietary trading systems, ensuring reliability and performance during critical market hours.
• Develop Python-based automation tools to streamline operational processes and enhance system observability.
• Collaborate with portfolio managers, researchers, and traders to address technical challenges effectively.
• Contribute to AI-driven alert triage and anomaly detection to modernize operational support.
• Maintain and improve monitoring dashboards using Grafana for proactive system monitoring.
• Document workflows and systems to enhance efficiency and reduce redundancy.
• Engage in on-call responsibilities to address critical production issues promptly.
• Support QA testing for new functionalities and liaise with external brokers on market data concerns.

Key Responsibilities & Duties

• Design and implement automation tools using Python to improve operational efficiency.
• Develop and maintain monitoring dashboards to ensure system reliability and performance.
• Collaborate with development teams to resolve complex technical challenges and optimize trading systems.
• Perform quality assurance testing for system updates and new features.
• Engage with external brokers and vendors to address order flow and market data issues.
• Document operational processes to improve efficiency and support automation initiatives.
• Participate in modernization efforts using AI and automation technologies.
• Respond to production incidents and collaborate with teams to resolve issues effectively.

Job Requirements

• Bachelor’s degree in IT, Computer Science, or a related field is required.
• Minimum of 5 years of experience in production or application support, preferably in financial services.
• Proficiency in Python for developing automation tools and scripts.
• Experience with FIX protocol, Linux, and SQL Server is essential.
• Knowledge of monitoring tools such as Grafana and familiarity with trading systems.
• Exposure to market data platforms, Git, and Jira is preferred.
• Interest in AI/LLM applications for operational contexts is advantageous.
• Ability to work under pressure during market hours and commitment to minimizing incidents.