Principal Safety Case Engineer

About us     Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.   Make Wayve the experience that defines your career!   The role We are looking for a Principal Safety Case Engineer to own the architecture, strategy and integrity of Wayve’s safety cases for our first products. This role sits independently from Engineering and Product and reports into Safety Management & Assurance, providing senior expert safety oversight while working closely with the teams responsible for designing, developing, validating and releasing the product. You will act as the architect of the safety case: defining the top-level claims, argumentation structure, evidence strategy and assurance approach that connect product intent, system behaviour, AI performance, engineering controls, validation and operational deployment into a coherent safety argument. You will provide independent challenge and advice, while enabling Engineering and Product teams to own and deliver the safety evidence required for their systems. What You’ll Be Doing Safety Case Strategy & Architecture Own the safety case strategy and architecture for Wayve’s robotaxi and OEM ADAS products. Define top-level safety claims, argumentation, evidence structures, and traceability from safety requirements through validation and deployment decisions. Develop safety arguments appropriate for AI-enabled autonomous driving, incorporating functional safety, SOTIF, AI safety, cybersecurity, validation, operational safety, and post-deployment monitoring. Evolve reusable safety case approaches as Wayve’s products, vehicle platforms, and evidence base mature. Product & Engineering Integration Partner with Product, Systems Engineering, AI/ML, Validation, Vehicle Engineering, Software, Hardware, and Operational Safety to define safety requirements and evidence expectations. Identify gaps, assumptions, and weaknesses in the safety argument early and drive resolution with accountable teams. Ensure product requirements, architecture, validation plans, and release criteria remain aligned with the safety case. Support technical and programme leaders in making proportionate, evidence-based safety decisions. Independent Safety Assurance Provide independent technical challenge of safety cases and supporting evidence. Assess whether safety arguments are coherent, complete, evidence-backed, and sufficient to support release or deployment. Highlight material gaps, uncertainties, dependencies, residual risks, and safety red lines. Provide clear recommendations to safety governance forums and senior leadership. Safety Leadership Build a common understanding of safety case principles across Wayve. Coach engineering and product leaders on structured safety argumentation, evidence quality, and traceability. Represent the safety case perspective in internal governance, customer, and technical discussions. Contribute to Wayve’s broader safety strategy and assurance capability. About You Essential Experience Deep experience developing or owning safety cases for complex safety-critical systems, ideally in autonomous vehicles, ADAS, robotics, aerospace, defence, or another software-intensive domain. Strong systems engineering background spanning requirements, architecture, verification, validation, and safety assurance. Proven ability to translate complex technical evidence into structured safety claims and arguments. Strong understanding of autonomous driving and AI/ML safety, including model performance, data, uncertainty, and limitations of conventional verification approaches. Experience partnering with AI/ML, engineering, systems, and product teams on safety-critical products. Strong knowledge of relevant standards, including ISO 26262, ISO 21448, ISO/PAS 8800, and ISO 3450x. Excellent technical communication and stakeholder management skills. Desirable Safety case experience with L2+/L3 ADAS or L4 ADS products. Experience with GSN or equivalent structured assurance methods. Safety evidence experience for end-to-end or foundation-model-ba