Technical Director, Safety Case

Overview

As Principal Safety Case Engineer, you own the safety-case architecture and integrity for Wayve’s robotaxi and OEM ADAS products. You will define top-level claims, evidence structures, and traceability, linking product intent, AI performance, and deployment into a coherent safety argument. You provide independent challenge while enabling teams to own their safety evidence. This role shapes Wayve’s safety strategy and assurance capability, with impact across governance, regulators, and customers.

Responsibilities

• Define safety case strategy and architecture for robotaxi and OEM ADAS products, including top-level claims, argumentation, and evidence structures
• Develop safety arguments for AI-enabled autonomous driving, covering functional safety, SOTIF, AI safety, cybersecurity, validation, and post-deployment monitoring
• Evolve reusable safety-case approaches as products and evidence bases mature
• Partner with Product, Systems Engineering, AI/ML, Validation, Vehicle Engineering, Software, Hardware, and Operational Safety to align requirements with safety evidence
• 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 align with the safety case
• Provide independent technical challenge of safety cases and supporting evidence
• Assess coherence, completeness, and sufficiency of safety arguments for release/deployment
• Highlight gaps, uncertainties, residual risks, and safety red lines with recommendations to governance forums
• Build a common understanding of safety-case principles and coach leaders on argumentation and evidence quality
• Represent safety-case perspectives in governance, customer, and technical discussions
• Contribute to Wayve’s broader safety strategy and assurance capability

Key requirements

• Deep experience owning safety cases for complex safety-critical systems, ideally in autonomous vehicles, ADAS, robotics, aerospace, or similar software-intensive domains
• Strong systems engineering background covering requirements, architecture, verification, validation, and safety assurance
• 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 verification limitations
• Experience partnering with AI/ML, engineering, systems, and product teams on safety-critical products
• Strong knowledge of ISO 26262, ISO 21448, ISO/PAS 8800, and ISO 3450x

• Excellent technical communication
• Stakeholder management
• Independent challenge and intellectual curiosity
• Safety-case architecture and argumentation
• Evidence-based safety planning
• AI safety and model uncertainty concepts

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