Validation Engineer - Multi-Agent AI Systems (f/m/x)

- Build and operate cloud-based validation environments for a multi-agent system that operates across ADAS, Infotainment and backend-service domains – defining test architectures, scenario pipelines, behavioural oracles and regression suites. - Design AI-assisted exploration strategies to navigate the semantic search space of the system under test: agent-based probing of behavioural boundaries, adaptive test strategies, and optimization techniques to surface edge cases and failure modes. - Develop coverage models and metrics for non-deterministic multi-agent systems and use them to steer test generation and assess release readiness. - Establish validation methodologies suited to stochastic AI behaviour: metamorphic testing, property-based testing, adversarial probing and acceptance criteria grounded in confidence intervals rather than binary pass/fail. - Build observability and diagnostics tooling for validation runs – distributed tracing, trajectory replay, automated failure clustering and root-cause triage to ensure that discovered issues can be rapidly understood and communicated to the design team. - Evaluate and select the LLMs/SLMs that power validation agents and test-generation systems, balancing latency, cost and accuracy for large-scale test campaigns. - Close the feedback loop between validation findings and system improvement by structuring discovered failures, coverage gaps and behavioural anomalies into actionable knowledge for the design and context-engineering teams.