Head of Software Development Engineer for Test (Cross Asset)

Company: IEX

Location: New York

Salary: $275k - $300k per year

Type: Full-time

Posted: 2026-07-10

About this role

  • IEX is seeking a senior Quality Engineering leader to scale and lead a best-in-class testing and automation program across our equities and options exchanges
  • Our QA function has grown quickly to support expanding product and platform capabilities
  • While we’ve made progress, much of our testing remains manual or partially automated, and our tooling and environments are not yet standardized across asset classes
  • We are looking for a leader who can unify and elevate our approach — driving a scalable, multi-asset testing strategy that supports continued growth
  • This role will own the end-to-end QA strategy across equities and options, modernize our automation framework, and establish a robust regression environment capable of supporting highly available, production-grade systems
  • You’ll partner closely with Engineering, Product, Market Operations, and Data teams, and play a critical role in improving reliability, efficiency, and release confidence across the organization
  • Own and execute the vision for a unified, cross-asset QA and automation strategy across equities and options
  • Lead the build-out and standardization of a scalable test harness that can be leveraged across both asset classes
  • Drive the organization from a partially automated environment toward a mature, automation-first testing model
  • Establish and enforce a comprehensive regression testing framework, including full regression suites run regularly against production-grade QA environments
  • Evaluate and evolve current tooling (e.g., Selenium, DSL frameworks, in-house tools) and determine the right long-term automation architecture
  • Ensure QA environments mirror production in strength and resiliency, while thoughtfully managing cost and infrastructure trade-offs
  • Partner with Engineering and Product to translate requirements into robust automated and manual test coverage
  • Leverage modern tools, including AI-assisted testing approaches, to improve efficiency and coverage
  • Unify and scale a ...

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