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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Consultant AD-Validation PM - SAE L4 Automated Driving & E2E AI Systems - **Company:** P3 Ingenieurgesellschaft mbH - **Location:** Stuttgart, Germany - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Continuous Integration, Machine Learning, ISO/IEC 15504, Sensor Fusion, Systems Architecture, Information Technology, Data Analytics, Lidar, Data Pipelines - **Published:** May 14, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=09c76ca6e0198939 ## About the Role Do you have experience in CI/CD?, * A university degree in Engineering, Computer Science, Artificial Intelligence or a related field * Solid understanding of AI/ML concepts for autonomous driving, including E2E vision-heavy approaches, data-driven development and AI-specific validation challenges * Deep understanding of the validation challenges of SAE Level 4 automated driving systems, including ODD definition, scenario coverage, residual risk assessment, safety case development and evidence-based release decisions * Hands-on experience with Simulations, SiL and HiL testing, ideally integrated into automated CI/CD environments * Strong technical understanding of AD system architectures, including modular pipelines, E2E AI models and hybrid architectures, as well as their impact on validation strategy and safety argumentation * Practical knowledge of camera, radar and lidar sensor characteristics, sensor fusion principles, calibration, synchronization, degradation effects and typical failure modes relevant for AD validation * Proven track record in high-reliability industries (automotive, aerospace, medical), with deep exposure to ASPICE, ISO 26262, SOTIF and homologation processes * Strong analytical and structuring skills to translate abstract safety, regulatory and AI risks into concrete validation strategies * Ability to work proactively and independently in agile, cross-functional teams, lead validation initiatives, and align multiple internal and external stakeholders ## Description * Define and operationalize holistic validation strategies for E2E AI-based AD systems, combining scenario-based testing, data-driven validation, simulation, and real-world testing * Translate regulatory, safety and quality requirements (ASPICE, ISO 26262, SOTIF, homologation, ISO PAS 8800) into executable validation concepts, KPIs and release criteria * Analyze the validation implications of key AD system components, including camera, radar, lidar, sensor fusion, localization, prediction, planning, control, data pipelines and runtime monitoring * Analyze / orchestrate SiL, HiL, MiL and vehicle-level testing and ensure seamless integration into automated CI/CD pipelines * Drive scalable validation approaches for AI models (incl. coverage metrics, corner-case detection, data curation strategies, and confidence arguments) * Define AI model validation KPIs and acceptance thresholds, including scenario coverage, ODD coverage, perception and planning performance, uncertainty calibration, robustness, latency, temporal consistency, rare-event behavior and regression stability * Align validation scope and evidence with Type Approval and AD Safety Management Systems (AD-SMS) * Act as central interface between AI development teams, system engineers, toolchain providers, test organizations, and external stakeholders (e.g. authorities, partners, suppliers) * Manage stakeholders at program and management level, including reporting, risk management, decision preparation and escalation * Proactively identify validation risks related to AI behavior, operational design domain (ODD) boundaries, and system interactions ## Related Videos - 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