Key Notes
Engineering-management experience leading and retaining a high-performing software or systems team is explicitly essential. Relevant expertise also includes embedded C++ credibility and real-time performance knowledge. You’ll establish Wayve’s Runtime Platform team and own its people, delivery, roadmap, middleware and observability. The London role is full time and hybrid, supporting AI Driver expansion across vehicle platforms and OEM programmes.
What You'll Work On
- Build and lead the Runtime Platform team through hiring, onboarding, coaching, performance management and structured career development.
- Own delivery, resourcing and roadmap commitments across application frameworks, middleware, inter-process communication, performance and observability foundations.
- Set technical direction for latency, profiling, real-time scheduling, embedded C++ and platform decisions with senior systems engineers.
- Establish CI, hardware-in-the-loop and internal quality gates that support rapid iteration across new vehicle-platform enablement work.
- Resolve dependencies with Vehicle Software, model developers, hardware teams and OEM programmes while acting as the team escalation point.
Why This Role Matters
- Frameworks, middleware and observability provide shared foundations for Wayve’s onboard software; runtime decisions shape how AI Driver components communicate, meet latency needs and expose performance problems.
- New vehicle platforms and OEM programmes reuse the same runtime foundations; incremental enablement and quality gates determine whether additions avoid unnecessary performance degradation.
What They Are Looking For
- Experience: Engineering management of a high-performing software or systems team, including hiring, coaching, feedback and retention, is explicitly essential.
- Experience: Relevant experience includes ownership of team roadmaps, prioritisation, resourcing and software delivery through others.
- Technical: Relevant technical skills include embedded C++, low-latency software, profiling, benchmarking and real-time scheduling on embedded Linux.
- Technical: Relevant technical skills include high-throughput middleware and inter-process communication across real-time or robotics systems.
- Stakeholder: Relevant stakeholder skills include direction-setting and delivery through influence across stakeholder teams.
- Preferred: Automotive, robotics, QNX, NVIDIA or Qualcomm platforms, profiling toolchains or observability-stack experience is desirable.