Software Engineer (Developer Productivity)

NJF Global Holdings Ltd · Chicago, United States

Software Engineer (Developer Productivity)

Salary: $250k-300k

Total compensation: very flexible - dependent on seniority, expectations and performance

I'm partnered with a leading high frequency trading firm hiring a Developer Productivity Engineer to build the tools and infrastructure that help engineers ship trading software faster and with more confidence.

The role

You’ll own the systems that sit between an engineer’s idea and production: build and test infrastructure, CI/CD, local environments and internal tooling. You’ll work directly with engineering teams across the firm, find where they lose time, and build platform-level fixes.

A growing part of the job is bringing AI-assisted engineering into everyday workflows. That means integrating coding agents, automating routine fixes and evaluating new AI developer tools as they appear.

What you’ll work on

• AI workflows: agent skills and configs, auto-remediation of build failures, and measuring impact on developer velocity
• Build and test acceleration: distributed caching, profiling and flaky test quarantine
• CI/CD: deployment pipelines, merge queues and automated releases
• Self-service dev environments, CLI tools, service templates and IDE integrations

What we’re looking for

• Strong Python
• Working knowledge of C++/Java
• Strong Linux fundamentals
• Experience with developer tooling, CI/CD or large-scale build infrastructure
• Hands-on use of AI coding tools (e.g. Claude Code, Codex) in real engineering work. No model training experience needed.
• Clear communicator, collaborative and low-ego
• Degree in CS or a related field preferred, though strong professional experience is a good substitute
• Large, well-regarded tech company background is a strong fit, especially with quick promotions. Trading experience is a bonus.

Seniority is flexible. Senior candidates should have deep, hands-on experience with AI-assisted engineering. Earlier-career candidates should be strong on engineering fundamentals and have some exposure to AI-assisted development.