Development jobs

Tomax is seeking a Senior QA Engineer to own end-to-end reliability across its higher-education assessment software. The role spans requirements review, AI-assisted test execution, complex defect investigation, and production quality.

Work on networking infrastructure software for a large-scale cloud platform. You will help define requirements, develop features, deploy software, and support operations.

Join a cloud infrastructure platform team developing firmware and low-level software for custom silicon and multi-core ARM systems. The role spans first-silicon bring-up, hardware validation, fleet testing, and production deployment.

A technology company is seeking a junior Software QA Engineer to test DPU software and SDK features, support release quality, and expand test automation.

An established networking technology company is seeking a senior software engineer to develop and maintain Python-based automation for AI Ethernet networking products.

Join an advanced computing team developing distributed training and inference systems across AI applications, networks, drivers, firmware, and programmable infrastructure.

Develop low-level, performance-oriented software for AI inference infrastructure and open-source acceleration libraries used across large-scale computing environments.

Join a video and multimedia architecture team developing software for video encoding and decoding systems. The role focuses on modern C++, Python, performance optimization, research-to-product delivery, and software quality. This is a hybrid position requiring four office days per week.

A global technology company is hiring an AI Infrastructure Engineer specializing in data center environments. The role includes intensive onboarding and product training through a full-time bootcamp lasting approximately one month. Successful completion of the training leads to placement in the role

Lead the internal AI strategy for a global financial technology organization. This newly created executive role will drive secure, measurable AI adoption across operations, engineering, knowledge management, and workforce productivity, reporting to the CEO.