Software Engineer, Machine Lifecycle

Tower Research Capital·New York·onsite
crypto:infraengineeringIC4Infrastructure Engineering
Compensation
Not disclosed
Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Summary: This role owns the journey of every machine in our fleet: from the moment a server is racked, cabled, and powered on, to the moment it is fully configured, validated, and available for users. Your mission is to make that journey zero-touch. You will design and build the automation pipeline that takes a machine through discovery, firmware and BIOS configuration, OS installation, configuration management, health validation and burn-in, and finally handoff into productio