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 Product Dependability TeamOur Product Dependability team connects Wayve's embodied AI technology with the demands of real-world automotive products. Working across systems engineering, safety, cybersecurity and data analysis, the team helps translate AI capabilities into dependable vehicle-level behavior and supports integration with our OEM partners.
Wayve is developing driver-out Robotaxi systems that bring together the AI Driver, vehicle platform, sensors and compute, safety mechanisms, Remote Assistance, fleet services and cloud operations. As a Systems Engineer, Robotaxi, you'll work closely alongside our lead Robotaxi System Architect, translating their reference architecture into clear, implementable functions, requirements, interfaces and verification-ready outputs for the areas you own.
Your day-to-day- Own systems engineering for defined parts of the Robotaxi architecture, translating use cases, operational concepts and constraints into requirements, interfaces, assumptions and verification-ready specifications.
- Work directly with OEMs, Tier 1 suppliers and Robotaxi operators to define system and product boundaries together, leading technical working sessions and design discussions.
- Support implementation through technical reviews, bring-up planning, issue triage and design-change impact analysis, escalating cross-domain or cross-program tradeoffs beyond your scope to the lead architect and relevant domain owners.
What you'll be working onYour scope covers how the Robotaxi system works as a safe, scalable driver-out service-from the vehicle, Automated Driving System (ADS) and onboard compute to offboard capabilities and the boundaries between Wayve and our partners.
You'll apply the Robotaxi reference architecture to real vehicle programs across sensors, compute, ECU topology, vehicle interfaces and degraded-operation behavior. Depending on your defined scope, this could include vehicle/ADS interfaces, Remote Assistance and offboard boundaries, or fleet and cloud integration.
You should apply if- You have direct, hands-on experience designing, integrating or deploying a Robotaxi or production-intent L4 driver-out system, with systems engineering experience spanning several domains across hardware, embedded software, autonomy, safety, offboard services or operations.
- You can turn use cases and operational concepts into functional decomposition, requirements, interfaces, assumptions, trade studies and verification intent, producing artifacts that teams can implement and verify.
- You've defined system and product boundaries across organizations, working directly with OEMs, Tier 1 suppliers, operators or technology partners while maintaining clear internal ownership.
- You bring practical vehicle or robotic-system integration experience and working knowledge of driver-out safety concepts, including redundancy, degraded operation, Minimum Risk Manoeuvre, fail-operational behavior, functional safety, SOTIF and safety-case evidence.
- You're comfortable owning a defined scope within a larger reference architecture, partnering with a lead architect and communicating complex designs clearly through documents, diagrams, requirements and technical reviews.
It would also be great if you bring experience with:- Robotaxi launch readiness and operations, including fleet services, Remote Assistance, teleoperation, depot operations, passenger systems or monitoring.
- Automotive E/E architecture, middleware and sensor/compute integration-including CAN, Automotive Ethernet, SOME/IP, AUTOSAR, DDS, QNX or Linux; calibration, synchronization, diagnostics and redundancy.
- Requirements and architecture tools such as Jama or MBSE/SysML, applying a reference architecture across multiple platforms, and understanding how AI model capability, generalization, compute headroom and evidence shape product architecture.
Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.
How we work - Locations & Flexible Working:This is a full-time role based in Sunnyvale, CA, with a hybrid working model.Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
The Interview Process:Our process is clear and respectful of your time:
- Initial call / recruiter screen 30 min
- Hiring Manager Interviews 1 hour
- Deep-dive technical interviews 2-3 hours
- Final interview: mission & values alignment 30 min
We'll always explain the format and work around your availability.
What's in it for you (Location dependant): Salaries benchmarked against the market annually
Meaningful equity, sharing in the ownership and long term success of Wayve
Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
Learning and development budgets with support for training, conferences and growth
Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more
A quick, honest note before you apply.
Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you'll help write it. That suits people who want real ownership more than people who need a settled structure from day one.
If that sounds like the kind of problem you want to spend your time on, we'd really like to hear from you.