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Own delivery strategy and execution for mission-critical, high-performance trading systems. Lead Agile ceremonies, translate trading requirements into backlogs, manage capacity and dependencies, maintain Jira and Confluence reporting, identify technical and resource blockers, and refine Agile processes for low-latency engineering teams.

Manage and support enterprise network infrastructure, VPN connectivity, firewalls, routing, switching, wireless networks, ISP links, and secure connectivity across offices, data centers, cloud environments, and remote users. Troubleshoot VPN and network issues, implement segmentation and access controls, coordinate with providers, support office expansions, maintain documentation and backups, and follow change-management procedures. Automate network monitoring, configuration backups, health checks, and other repetitive tasks using scripting and network automation tools.

Designs, deploys, operates, and troubleshoots ultra-low-latency network infrastructure for quantitative trading. Responsibilities include exchange and market-data connectivity, data-center and colocation networking, multicast and routing, PTP synchronization, performance monitoring, hardware installation, production changes, documentation, incident analysis, and automation using Python, Bash, or Ansible.

Monitor production and trading systems, respond to alerts and outages, triage issues across applications, databases, and infrastructure, coordinate incident resolution, conduct root-cause analysis, and implement lasting fixes. Build automation to reduce manual intervention, improve monitoring, logging, and alerting, and maintain operational runbooks and SLO/SLA metrics.

Build and optimize high-performance, low-latency software for quantitative research and live trading. Responsibilities include developing distributed systems in C++, working with Linux, networking, concurrency, and multithreading, profiling and optimizing performance, debugging production systems, and owning solutions from design through deployment and monitoring. Collaborate with quantitative researchers and engineers on reliable infrastructure, developer tools, and intelligent automation.

Conduct quantitative research for systematic trading by formulating hypotheses, analyzing massive market datasets, developing predictive models and signals, and validating strategies through rigorous backtesting and statistical testing. Investigate market microstructure, distinguish genuine patterns from noise, build AI-powered research tools, and collaborate with technologists to move promising ideas into production and live trading. The role requires ownership, rigorous reasoning, strong communication, and comfort with ambiguous research problems.

Seeking a Software Engineer to build and maintain scalable backend applications, troubleshoot issues, and collaborate with other team members in a fast-paced trading environment.

The Quantitative Researcher will develop trading models, analyze financial datasets, and support traders using advanced mathematical techniques.

As a Machine Learning Researcher, you'll lead research in applying ML to trading problems, develop deep learning models, and collaborate with quant researchers.

Design and implement a high-frequency automated trading system, optimize performance, and support modules, while aiding in team growth.