Solution Architect

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 Architecture and Safety Teams Our Product Architecture and Safety team brings Wayve’s AI Driver into real-world automotive products, connecting our core autonomous driving technology with the vehicle platforms of our OEM and Tier 1 partners. As a Solution Architect, you’ll work at the boundary between Wayve’s core AI Driver architecture and customer vehicle systems. You’ll help define how our software integrates with sensors, vehicle signals, middleware and electronic control units (ECUs), accounting for timing, diagnostics, safety assumptions, data logging and validation. Working across Product, Software Architecture, Hardware, Calibrations, System Safety, Validation and Field Application Engineering, you’ll help deliver safe, efficient and consistent integrations while preserving a scalable core product architecture.   🧠 Your day-to-day - Define and manage the technical architecture for customer vehicle integrations, focusing on the interfaces between Wayve software and OEM or Tier 1 systems. - Partner with Product Management to translate product requirements and customer program needs into clear, actionable technical specifications. - Turn ambiguous customer discussions into explicit ownership boundaries, interface contracts, assumptions, dependencies and open technical decisions. - Work with Software Architects to assess feasibility and align customer integration needs with Wayve’s core architecture. - Coordinate with Validation Engineers to define integration test requirements and ensure requirements are verifiable. - Represent Wayve in OEM and Tier 1 technical discussions, keeping internal teams and external partners aligned on architecture, integration plans and technical risks. 🧩 What you’ll be working on - Software–vehicle interfaces: Define how Wayve’s AI Driver connects with vehicle platforms, including sensors, signals, middleware, ECU constraints, real-time execution, diagnostics and data logging. - Integration boundaries and ownership: Establish what is Wayve-owned, partner-owned, jointly defined or out of scope, making responsibilities and dependencies clear across each customer program. - Scalable customer integrations: Address customer-specific needs without unnecessarily fragmenting Wayve’s core product architecture. - Technical specifications and documentation: Develop interface specifications, integration guides, architecture diagrams, ownership boundary definitions and decision records. - Validation-ready architecture: Translate integration needs and safety assumptions into clear requirements that can be tested and verified. - Program planning and risk management: Identify integration complexity, technical gaps, dependencies, risks and required partner deliverables to support realistic planning and informed decisions.   🙌 You should apply if - You have systems and software architecture experience in ADAS, autonomous driving, embedded software or vehicle systems, particularly at the software–vehicle interface. - You understand vehicle electronics and embedded systems, including ECU integration, real-time execution, timing, diagnostics and automotive technologies such as CAN, Automotive Ethernet, SOME/IP or AUTOSAR. - You’ve worked with automotive OEMs or Tier 1 suppliers, translating customer needs into clear technical specifications, interface contracts, ownership boundaries and validation-ready requirements. - You collaborate effectively across product, software, hardware, safety, validation and customer-facing teams, aligning technical decisions from individual components through to complete vehicle systems. - You’re comfortable owning ambiguous technical problems independently, identifying risks and dependencies, and communicating architectural decisions clearly through documentation, diagrams and technical discussions. It would also be great if you bring: - A bachelor’s or master’s degree in Computer Science, Electrical Engineering or a related field. - Experience working within an automotive Tier 1 supplier or delivering automotive OEM integration projects. - Knowledge of generative AI, large language models and transformer architectures. - Familiarity with end-to-end approaches to autonomous driving. - Hands-on experience with embedded Linux, QNX, Adaptive AUTOSAR, DDS, SOME/IP or custom automotive middleware. - Experience integrating sensors such as cameras, radar, IMU and GNSS, including calibration, timestamping and synchronisation.   🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and