Head of Software Engineering [Riyadh – GPU] Full Time

*This role requires relocation to Riyadh, KSA*

We’re partnering with a fast-scaling deep tech startup building next-generation AI infrastructure, combining cutting-edge hardware and software to deliver high-performance, on-premise AI compute solutions.

Backed by leading enterprise customers and operating in one of the most important technology categories of the next decade, this company is now looking for a Head of Engineering to build and lead its engineering function from the ground up.

The Opportunity

This is a rare chance to step into a foundational leadership role at an early stage and shape the entire engineering organisation.

You’ll be taking ownership of both hardware and software engineering, while remaining hands-on technically. This isn’t a pure management role; you’ll be expected to contribute directly to architecture, code, and system design. Over time, you’ll scale the team, introduce structure, and build a high-performing engineering culture across multiple disciplines.

The Role

• Own engineering across hardware + software
• Stay hands-on (coding, architecture, system design)
• Scale and structure the team from the ground up
• Drive development across infrastructure, low-level systems, and performance optimisation

What They’re Looking For

• Proven experience leading multiple teams or managers in complex engineering environments
• Strong hands-on technical background.
• Full-stack systems exposure, from high-level applications to low-level systems
• Experience working in Linux-based environments and infrastructure platforms
• Proficiency in at least one: Python, C++, C, or Node.js
• Background in compute platforms, distributed systems, or GPU-related infrastructure
• Experience in hardware-adjacent environments (e.g. embedded systems, consoles, SDKs, cloud infrastructure)
• Genuine passion for systems, performance, and hardware

Nice to Have

• Experience with GPU acceleration, CUDA, or low-level performance optimisation
• Exposure to ML systems, inference engines, or model training workflows
• Knowledge of hardware design, cooling systems, or physical system constraints
• Experience with manufacturing, supply chain, or system assembly
• Strong product mindset with an eye for performance and design