Engineering Manager - Compute and Data Platform (AI Platform)

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Behind Wayve’s embodied AI is the compute and data infrastructure that enables our ML engineers and researchers to train and run increasingly capable models. Our Compute Foundations team builds and operates the large-scale cloud infrastructure that makes this possible, spanning GPU compute, storage, workload scheduling and the platforms that support training and inference. You’ll lead this London-based team through its next phase of growth, helping build and maintain a reliable, high-performance, multi-cloud and multi-region platform. The challenges go beyond provisioning resources: they include scheduling workloads across different GPU architectures, keeping valuable compute available, and moving data efficiently while managing costs. You’ll lead a team working with state-of-the-art tooling to tackle infrastructure challenges found only at the world’s leading AI companies, building the platform that enables Wayve to develop its AI Driver.   🧠 Your day-to-day People leadership will be your first priority. You’ll coach and develop engineers, set clear expectations, manage performance. You’ll build technical leadership within the team, giving engineers the support and ownership they need to grow. You will guide the growth of the team through hiring and onboarding. Alongside this, you will own project prioritisation and roadmap planning, aligning priorities and delivery plans with stakeholders across Wayve. Your goal is to maximise the impact of the team in alignment with the department and company objectives. You will provide visibility into the state of systems you own through clear KPIs and dashboards. Leading a highly technical team, you’ll bring the technical judgement to guide complex infrastructure decisions and turn competing needs into a clear roadmap. Working with technical leads, partner teams and cloud providers, you’ll balance reliability, performance, capacity and cost, and help the team deliver sustainably.   🧩 What you’ll be working on - Leading and developing the team: Coach engineers through regular feedback and one-to-ones, manage performance, support career development and build a healthy, performant and accountable team. - Hiring and building technical leadership: Lead hiring and onboarding as the team expands, and develop technical leads who can take ownership of key areas of the platform. - Driving the roadmap and delivery: Translate training and inference needs into priorities, align commitments with available resources, and surface risks and dependencies early. - Scaling cloud compute: Guide the evolution and operation of a multi-cloud, multi-region training and inference platform, including the adoption of new compute architectures (Nvidia Hopper, Blackwell; Qualcomm). - Improving scheduling and availability: Oversee Kubernetes-based infrastructure and queuing and scheduling systems, enabling workloads to use the right resources across heterogeneous GPU environments. - Planning capacity and cost: Partner with stakeholders and cloud providers on compute and storage forecasts, accounting for resource lead times, performance requirements and cost trade-offs. - Ensuring efficient storage across clouds: Guide distributed storage and caching approaches that improve data access and reduce unnecessary duplication and cross-cloud transfer costs.   🙌 You should apply if - You have a strong track record of managing and developing an infrastructure, platform or distributed systems engineering team, including hiring, coaching, performance management and career development. - You have delivered through others, owning team priori