Head of Software Engineering [GPU]

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

The Opportunity

We’re hiring a Head of Engineering to lead the development of a platform that operates independently of the underlying hardware. This is a critical leadership role focused on building a developer-first system that enables flexibility, performance, and global adoption.

The Role

• Lead the development of a standalone orchestration platform
• Define and execute the strategy to decouple software from hardware environments
• Build and scale a developer-focused platform and ecosystem
• Drive integrations with OEMs, cloud providers, and infrastructure partners
• Own platform adoption and commercialisation through partnerships
• Stay hands-on where needed—maintaining technical credibility with engineering teams
• Engage with customers and partners at both technical and executive levels

What They’re Looking For

• Minimum 10+ years in software engineering with at least 4 years leading teams of 5 or more engineers.
• Deep expertise in at least two of: AI infrastructure, MLOps, distributed systems, GPU-accelerated workloads, HPC, or runtime systems programming
• Strong background in GPU scheduling, KV-cache management, or LLM serving optimisation
• Hands-on experience deploying and optimising AI infrastructure at production scale, ideally with multiple inference engines, utilities, and training frameworks.
• Proven ability to ship production software through a full release cycle, not just a prototype
• Strong fluency in Python, C++, and a systems language (Rust, Go, or modern C); comfort with JavaScript or TypeScript for tooling
• Solid grounding in Linux internals, containers, GPU drivers, CUDA, and observability tooling

Nice to Have

• Direct experience with sovereign AI, on-premise LLM deployment, air-gapped systems, or AI in regulated industries (defence, energy, government, finance, healthcare)
• Open-source contributions in the AI infrastructure space
• Prior experience as a founding engineer or senior engineer at a deep-tech startup that reached commercial GA
• Experience with security primitives: hardware fingerprinting, license enforcement, software protection, code obfuscation