Key Notes
ADAS feature ownership runs from specification through production for functions including High Beam Assist, Blind Spot Monitoring and Cross Traffic Alert. The role needs experience defining and delivering ADAS features, automotive requirements and validation processes, OEM representation and hands-on technical trade-off work. This full-time London appointment follows a hybrid working policy with core hours.
What You'll Work On
- Own named ADAS features from concept to production, monitoring specifications, delivery timing, lifecycle changes and deviations against commitments.
- Create feature specifications with engineering owners, provide early feedback and participate in testing, evaluation and validation throughout development.
- Represent OEM requirements internally and harmonise requests across customers to maximise reusable ADAS assets and programme scalability.
- Maintain feature roadmaps, coordinate OEM, Product and Engineering teams and address technical or delivery risks before escalation.
Why This Role Matters
- High Beam Assist, Blind Spot Monitoring and Cross Traffic Alert depend on agreed specifications, testing and validation to match OEM requirements at production delivery.
- OEM programme requirements are harmonised against Wayve’s internal roadmap, limiting customer-specific fragmentation while preserving the agreed behaviour of each driver-assistance feature.
What They Are Looking For
- Experience: Expertise specifying and facilitating ADAS feature delivery from concept to production is required.
- Domain: Automotive requirements management, V-model, ASPICE, quality and validation experience is required.
- Stakeholder: Ability to represent OEM needs, negotiate requirements and align customers with internal teams is required.
- Technical: Understanding of ADAS trade-offs with hands-on testing, evaluation and validation involvement is required.
- Preferred: Delivery of complete ADAS features into large-scale production automotive programmes is desirable.
- Preferred: Automotive quality and safety standards, machine learning, LLMs or generative-AI methods are desirable.