Engineering Manager - Compute and Data Platform (AI Platform) at Wayve
At a glance
- Company
- Wayve
- Location
- United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 10+ years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this Wayve job
- 🏢 Wayve has 44 jobs here, 42 with visa sponsorship see all
- 📊 14 Engineering Manager jobs in the United Kingdom in the last 60 days see them
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask Wayve if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Lead and develop the London-based Compute Foundations team: coaching, one-to-ones, performance reviews and career growth.
- Recruit and build technical leadership to scale ownership across GPU compute, scheduling and storage domains.
- Own roadmap planning, prioritisation and delivery; align team commitments with company ML training and inference needs.
- Define and track KPIs and dashboards to provide clear visibility into system health, capacity and cost.
- Make technical trade-offs across reliability, performance, capacity and cost; coordinate with cloud providers and partners.
- Guide design and operation of a multi-cloud, multi-region platform: workload scheduling, GPU lifecycle, data locality and caching.
Requirements:
- Proven experience managing infrastructure, platform or distributed-systems teams at scale.
- Deep familiarity with Kubernetes and workload scheduling (e.g., Kueue) and large-scale GPU training/inference infrastructure.
- Practical experience with multi-cloud operations, capacity forecasting, cloud cost modelling and storage/distributed systems.
- Strong technical judgement to balance competing priorities and drive sustainable operational practices.
- Experience hiring and growing engineers into technical leadership roles and communicating with senior stakeholders and providers.
Responsibilities
Lead and grow the London-based Compute Foundations team, including coaching, hiring, performance management, and developing technical leaders. Own the team roadmap and guide the operation and evolution of multi-cloud compute, scheduling, storage, capacity, and cost systems for AI training and inference.
Requirements
Candidates should have a strong track record managing infrastructure, platform, or distributed-systems teams, along with substantial experience in Kubernetes and workload scheduling. They should understand large-scale GPU infrastructure and cloud capacity, reliability, performance, and cost trade-offs, and be able to lead technical decisions and communicate effectively with stakeholders and providers.
Key skills
- People Management — in 16 other listings on The Stack
- Hiring And Onboarding — in 3 other listings on The Stack
- Performance Management — in 28 other listings on The Stack
- Team Development — in 7 other listings on The Stack
- Roadmap Planning — in 22 other listings on The Stack
- Kubernetes — in 585 other listings on The Stack
- Workload Scheduling — not in any other listing on The Stack
- GPU Infrastructure — in 6 other listings on The Stack
- Cloud Infrastructure
- Multi-Cloud Platforms
- Distributed Systems
- Capacity Planning
- Cloud Cost Management
- Distributed Storage
- Technical Leadership
- Stakeholder Communication
On The Stack (as of 2026-11-05)
Frequently asked questions about Wayve
Is this Engineering Manager - Compute and Data Platform (AI Platform) role still open?
It was posted on 2026-11-04 and is listed as active on The Stack. Confirm on Wayve's application page before applying.
Does Wayve offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Wayve's site.
Where is this role located?
The listing gives the location as United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: People Management, Hiring And Onboarding, Performance Management, Team Development, Roadmap Planning, Kubernetes, Workload Scheduling, GPU Infrastructure, Cloud Infrastructure, Multi-Cloud Platforms, Distributed Systems, Capacity Planning, Cloud Cost Management, Distributed Storage, Technical Leadership, Stakeholder Communication.